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6. Philosophy of Artificial Intelligence (Philosophy of Artificial Intelligence on PhilPapers)

• Can Machines Think? [185]
• The Turing Test [52]
• Godelian arguments [30]
• The Chinese Room [39]
• Machine Consciousness [32]
• Machine Mentality, Misc [32]
• Computation and Representation [81]
• Symbols and Symbol Systems [16]
• Computational Semantics [12]
• Implicit/Explicit Rules and Representations [10]
• AI without Representation? [10]
• Computation and Representation, Misc [8]
• Philosophy of Connectionism [100]
• Connectionism and Compositionality [21]
• Representation in Connectionism [20]
• Connectionism and Eliminativism [5]
• The Connectionist/Classical Debate [14]
• Subsymbolic Computation [5]
• Philosophy of Connectionism, Misc [21]
• Philosophy of Connectionism, Foundational Empirical Issues [14]
• Special Topics in AI [93]
• Cybernetics [0]
• Dynamical Systems [34]
• The Nature of AI [6]
• The Frame Problem [10]
• AI Methodology [17]
• Robotics [22]
• Computationalism [84]
• Computation and Physical Systems [34]
• Computation and Physical Systems, Misc [0]
• Analog and Digital Computation [5]
• Computers [0]
• Implementing Computations [0]
• Noncomputable Processes [0]
• Pancomputationalism [0]
• Quantum Computation [2]
• Philosophy of AI, Miscellaneous [30]
• Philosophy of AI, General Works [0]
• Philosophy of AI, Misc [0]

Can Machines Think?

The Turing Test

• Varol Akman & Patrick Blackburn (2000). Editorial: Alan Turing and artificial intelligence.   (Abstract & more)
  Abstract: Department of Computer Engineering, Bilkent University, 06533 Ankara, Turkey E-mail: akman@cs.bilkent.edu.tr; http://www.cs.bilkent.edu.tr/?akman..
  Additional links for this entry:
  http://citeseer.ist.psu.edu/377438.html
  http://portal.acm.org/citation.cfm?id=595992
  http://cogprints.ecs.soton.ac.uk/archive/00001058/00/intro.ps
  http://www.cs.bilkent.edu.tr/~akman/jour-papers/jolli/jolli2000.pdf
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:1058
  http://www.springerlink.com/content/rm454307n5h9k066/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=269485&PDF=1
  http://www.springerlink.com/index/RM454307N5H9K066.pdf
  http://www.ingentaconnect.com/content/klu/jlli/2000/00000009/00000004/00269485
  
• John Barresi (1987). Prospects for the cyberiad: Certain limits on human self-knowledge in the cybernetic age.   (More)
  Additional links for this entry:
  http://www3.interscience.wiley.com/cgi-bin/fulltext/120019196/PDFSTART
  
• Ned Block (1981). Psychologism and behaviorism.   (Abstract & more)
  Abstract: Let psychologism be the doctrine that whether behavior is intelligent behavior depends on the character of the internal information processing that produces it. More specifically, I mean psychologism to involve the doctrine that two systems could have actual and potential behavior _typical_ of familiar intelligent beings, that the two systems could be exactly alike in their actual and potential behavior, and in their behavioral dispositions and capacities and counterfactual behavioral properties (i.e., what behaviors, behavioral dispositions, and behavioral capacities they would have exhibited had their stimuli differed)--the two systems could be alike in all these ways, yet there could be a difference in the information processing that mediates their stimuli and responses that determines that one is not at all intelligent while the other is fully intelligent
  Additional links for this entry:
  http://www.nyu.edu/gsas/dept/philo/faculty/block/papers/Psychologism.pdf
  http://www.nyu.edu/gsas/dept/philo/faculty/block/papers/Psychologism.htm
  http://links.jstor.org/sici?sici=0031-8108(198101)90:1<5:PAB>2.0.CO;2-J
  http://www.jstor.org/sici?sici=0031-8108(198101)90:1<5:PAB>2.0.CO;2-J
  http://www.jstor.org/stable/pdfplus/2184371.pdf
  http://philosophy.wisc.edu/shapiro/Phil951/Block.pdf
  
• Selmer Bringsjord (2000). Animals, zombanimals, and the total Turing test: The essence of artificial intelligence.   (More)
  Additional links for this entry:
  http://portal.acm.org/citation.cfm?id=595843.595993
  http://citeseer.ist.psu.edu/bringsjord00animals.html
  http://www.rpi.edu/~faheyj2/SB/SELPAP/ZOMBANIMALS/zombanimals2.pdf
  http://www.kluweronline.com/article.asp?PIPS=269486&PDF=1
  http://www.springerlink.com/index/TV852P4283211235.pdf
  http://www.ingentaconnect.com/content/klu/jlli/2000/00000009/00000004/00269486
  
• Selmer Bringsjord, P. Bello & David A. Ferrucci (2001). Creativity, the Turing test, and the (better) Lovelace test.   (Abstract & more)
  Abstract:   The Turing Test (TT) is claimed by many to be a way to test for the presence, in computers, of such ``deep'' phenomena as thought and consciousness. Unfortunately, attempts to build computational systems able to pass TT (or at least restricted versions of this test) have devolved into shallow symbol manipulation designed to, by hook or by crook, trick. The human creators of such systems know all too well that they have merely tried to fool those people who interact with their systems into believing that these systems really have minds. And the problem is fundamental: the structure of the TT is such as to cultivate tricksters. A better test is one that insists on a certain restrictive epistemic relation between an artificial agent (or system) A, its output o, and the human architect H of A – a relation which, roughly speaking, obtains when H cannot account for how A produced o. We call this test the ``Lovelace Test'' in honor of Lady Lovelace, who believed that only when computers originate things should they be believed to have minds
  Additional links for this entry:
  http://portal.acm.org/citation.cfm?id=596904
  http://citeseer.ist.psu.edu/bringsjord00creativity.html
  http://www.rpi.edu/~faheyj2/SB/SELPAP/DARTMOUTH/lt3.pdf
  http://www.springerlink.com/content/content/nrvl130w46xj6g22/fulltext.pdf
  http://www.springerlink.com/content/nrvl130w46xj6g22/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=319539&PDF=1
  http://www.springerlink.com/index/NRVL130W46XJ6G22.pdf
  http://www.ingentaconnect.com/content/klu/mind/2001/00000011/00000001/00319539
  
• Andrew Clifton (ms). Blind man's bluff and the Turing test.   (Abstract & more)
  Abstract: It seems plausible that under the conditions of the Turing test, congenitally blind people could nevertheless, with sufficient preparation, successfully represent themselves to remotely located interrogators as sighted. Having never experienced normal visual sensations, the successful blind player can prevail in this test only by playing a 'lying game'—imitating the phenomenological claims of sighted people, in the absence of the qualitative visual experiences to which such statements purportedly refer. This suggests that a computer or robot might pass the Turing test in the same way, in the absence not only of visual experience, but qualitative consciousness in general. Hence, the standard Turing test does not provide a valid criterion for the presence of consciousness. A 'sensorimetric' version of the Turing test fares no better, for the apparent correlations we observe between cognitive functions and qualitative conscious experiences seems to be contingent, not necessary. We must therefore define consciousness not in terms of its causes and effects, but rather, in terms of the distinctive properties of its content, such as its possession of qualitative character and apparent intrinsic value—the property which confers upon consciousness its moral significance. As a means of determining whether or nor a machine is conscious, in this sense, an alternative to the standard Turing test is proposed
  Additional links for this entry:
  http://cogprints.org/3480/01/Blind_mans_bluff_and_the_Turing_test.pdf
  
• B. Jack Copeland (2000). The Turing test.   (Abstract & more)
  Abstract:   Turing''s test has been much misunderstood. Recently unpublished material by Turing casts fresh light on his thinking and dispels a number of philosophical myths concerning the Turing test. Properly understood, the Turing test withstands objections that are popularly believed to be fatal
  Additional links for this entry:
  http://books.google.com/books?hl=en&lr=&id=5BJaXSedqfIC&oi=fnd&pg=PA519&ots=rzjaTOxdpq&sig=slbbZKdPbjoJsVO44CwfWr3oSMo
  http://books.google.com/books?hl=en&lr=&id=ECj6fuEMdp0C&oi=fnd&pg=PA519&ots=blQICrgbeX&sig=4woWcfbL_fO5zip_aVT89VSM390
  http://www.springerlink.com/content/content/w103433h4g273841/fulltext.pdf
  http://www.springerlink.com/content/w103433h4g273841/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=319531&PDF=1
  http://www.springerlink.com/index/W103433H4G273841.pdf
  http://www.ingentaconnect.com/content/klu/mind/2000/00000010/00000004/00319531
  
• Dr Louis J. Cutrona, Jr (ms). Zombies in Searle's chinese room: Putting the Turing test to bed.   (Abstract & more)
  Abstract: Searle's discussions over the years 1980-2004 of the implications of his Chinese Room Gedanken experiment are frustrating because they proceed from a correct assertion: (1) Instantiating a computer program is never by itself a sufficient condition of intentionality; and an incorrect assertion: (2) The explanation of how the brain produces intentionality cannot be that it does it by instantiating a computer program. In this article, I describe how to construct a Gedanken zombie Chinese Room program that will pass the Turing test and at the same time unambiguously demonstrates the correctness of (1). I then describe how to construct a Gedanken Chinese brain program that will pass the Turing test, has a mind, and understands Chinese, thus demonstrating that (2) is incorrect. Searle's instantiation of this program can and does produce intentionality. Searle's longstanding ignorance of Chinese is simply irrelevant and always has been. I propose a truce and a plan for further exploration
  Additional links for this entry:
  http://cogprints.org/4636/01/TR-05-002.pdf
  
• Bruce Edmonds (2000). The constructability of artificial intelligence (as defined by the Turing test).   (Abstract & more)
  Abstract: The Turing Test (TT), as originally specified, centres on theability to perform a social role. The TT can be seen as a test of anability to enter into normal human social dynamics. In this light itseems unlikely that such an entity can be wholly designed in anoff-line mode; rather a considerable period of training insitu would be required. The argument that since we can pass the TT,and our cognitive processes might be implemented as a Turing Machine(TM), that consequently a TM that could pass the TT could be built, isattacked on the grounds that not all TMs are constructible in a plannedway. This observation points towards the importance of developmentalprocesses that use random elements (e.g., evolution), but in these casesit becomes problematic to call the result artificial. This hasimplications for the means by which intelligent agents could bedeveloped
  Additional links for this entry:
  http://www.springerlink.com/content/u121t003r65q802w/fulltext.pdf
  
• Gerald J. Erion (2001). The cartesian test for automatism.   (Abstract & more)
  Abstract:   In Part V of his Discourse on the Method, Descartes introduces a test for distinguishing people from machines that is similar to the one proposed much later by Alan Turing. The Cartesian test combines two distinct elements that Keith Gunderson has labeled the language test and the action test. Though traditional interpretation holds that the action test attempts to determine whether an agent is acting upon principles, I argue that the action test is best understood as a test of common sense. I also maintain that this interpretation yields a stronger test than Turing's, and that contemporary artificial intelligence should consider using it as a guide for future research
  Additional links for this entry:
  http://books.google.com/books?hl=en&lr=&id=ECj6fuEMdp0C&oi=fnd&pg=RA4-PA241&ots=blQICrghbY&sig=dV16mfWZM_Qoj6YrtNA26fR1IZk
  http://books.google.com/books?hl=en&lr=&id=5BJaXSedqfIC&oi=fnd&pg=RA5-PA241&ots=rzjaTOxjmr&sig=MTJT29H2X-bBW0rfBOaTIEju52o
  http://www.springerlink.com/content/content/h814j04926567527/fulltext.pdf
  http://www.springerlink.com/content/h814j04926567527/fulltext.pdf
  http://www.springerlink.com/index/H814J04926567527.pdf
  http://www.ingentaconnect.com/content/klu/mind/2001/00000011/00000001/00319541
  
• Luciano Floridi (2005). Consciousness, agents and the knowledge game.   (Abstract & more)
  Abstract: This paper has three goals. The first is to introduce the “knowledge game”, a new, simple and yet powerful tool for analysing some intriguing philosophical questions. The second is to apply the knowledge game as an informative test to discriminate between conscious (human) and conscious-less agents (zombies and robots), depending on which version of the game they can win. And the third is to use a version of the knowledge game to provide an answer to Dretske’s question “how do you know you are not a zombie?”
  Additional links for this entry:
  http://philsci-archive.pitt.edu/archive/00002546/
  http://philsci-archive.pitt.edu/archive/00002546/01/caatkg.pdf
  http://www.springerlink.com/content/f52pq39812453221/fulltext.pdf
  http://www.springerlink.com/index/F52PQ39812453221.pdf
  http://www.ingentaconnect.com/content/klu/mind/2005/00000015/F0020003/00009005
  
• Robert M. French (2000). Peeking behind the screen: The unsuspected power of the standard Turing test.   (Abstract & more)
  Abstract: No computer that had not experienced the world as we humans had could pass a rigorously administered standard Turing Test. We show that the use of “subcognitive” questions allows the standard Turing Test to indirectly probe the human subcognitive associative concept network built up over a lifetime of experience with the world. Not only can this probing reveal differences in cognitive abilities, but crucially, even differences in _physical aspects_ of the candidates can be detected. Consequently, it is unnecessary to propose even harder versions of the Test in which all physical and behavioral aspects of the two candidates had to be indistinguishable before allowing the machine to pass the Test. Any machine that passed the “simpler” symbols- in/symbols-out test as originally proposed by Turing would be intelligent. The problem is that, even in its original form, the Turing Test is already too hard and too anthropocentric for any machine that was not a physical, social, and behavioral carbon copy of ourselves to actually pass it. Consequently, the Turing Test, even in its standard version, is not a reasonable test for general machine intelligence. There is no need for an even stronger version of the Test
  Additional links for this entry:
  http://citeseer.ist.psu.edu/french00peeking.html
  http://www.u-bourgogne.fr/LEAD/people/french/peeking.pdf
  http://www.phil.canterbury.ac.nz/tom_bestor/e-texts/French, Robert - Peeking behind the screen (2000) peeking.pdf
  http://www.informaworld.com/index/24PHYLU4NX08NHQF.pdf
  http://www.ingentaconnect.com/content/tandf/teta/2000/00000012/00000003/art00006
  
• Robert M. French (1990). Subcognition and the limits of the Turing test.   (More)
  Additional links for this entry:
  http://philosophy.wisc.edu/Shapiro/Phil554/PAPERS/French.pdf
  http://www.phil.canterbury.ac.nz/tom_bestor/e-texts/French, Robert - Subcognition and the Limits of the Turing Test (1990) turing.pdf
  http://links.jstor.org/sici?sici=0026-4423(199001)2:99:393<53:SATLOT>2.0.CO;2-E
  http://www.jstor.org/sici?sici=0026-4423(199001)2:99:393<53:SATLOT>2.0.CO;2-E
  http://www.jstor.org/stable/pdfplus/2254890.pdf
  
• Robert French (1996). The inverted Turing test: How a mindless program could pass it.   (Abstract & more)
  Abstract: This commentary attempts to show that the inverted Turing Test (Watt 1996) could be simulated by a standard Turing test and, most importantly, claims that a very simple program with no intelligence whatsoever could be written that would pass the inverted Turing test. For this reason, the inverted Turing test in its present form must be rejected
  Additional links for this entry:
  http://www.u-bourgogne.fr/LEAD/people/french/invturing.pdf
  
• Robert French (2000). The Turing test: The first fifty years.   (Abstract & more)
  Abstract: The Turing Test, originally proposed as a simple operational definition of intelligence, has now been with us for exactly half a century. It is safe to say that no other single article in computer science, and few other articles in science in general, have generated so much discussion. The present article chronicles the comments and controversy surrounding Turing's classic article from its publication to the present. The changing perception of the Turing Test over the last fifty years has paralleled the changing attitudes in the scientific community towards artificial intelligence: from the unbridled optimism of 1960's to the current realization of the immense difficulties that still lie ahead. I conclude with the prediction that the Turing Test will remain important, not only as a landmark in the history of the development of intelligent machines, but also with real relevance to future generations of people living in a world in which the cognitive capacities of machines will be vastly greater than they are now
  Additional links for this entry:
  http://citeseer.ist.psu.edu/french00turing.html
  http://srsc.ulb.ac.be/cogsci/papers/TICS-French_turing.pdf
  http://www.u-bourgogne.fr/LEAD/people/french/TICS_turing.pdf
  http://www.phil.canterbury.ac.nz/tom_bestor/e-texts/French, Robert - The Turing Test -The First Fifty Years (2000) TICS_turing.pdf
  http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=10689346&dopt=Citation
  http://www.ingentaconnect.com/content/els/13646613/2000/00000004/00000003/art01453
  
• Stevan Harnad & Itiel Dror (2006). Distributed cognition: Cognizing, autonomy and the Turing test.   (Abstract & more)
  Abstract: Some of the papers in this special issue distribute cognition between what is going on inside individual cognizers' heads and their outside worlds; others distribute cognition among different individual cognizers. Turing's criterion for cognition was individual, autonomous input/output capacity. It is not clear that distributed cognition could pass the Turing Test
  Additional links for this entry:
  http://cogprints.org/4840/04/discintro.rtf
  http://cogprints.org/4840/03/discintro.pdf
  http://cogprints.org/4840/02/discintro.html
  http://eprints.ecs.soton.ac.uk/12368/02/discintro.pdf
  http://dialnet.unirioja.es/servlet/articulo?codigo=2196285
  http://www.ingentaconnect.com/content/jbp/pc/2006/00000014/00000002/art00002
  
• Stevan Harnad (1995). Does mind piggyback on robotic and symbolic capacity?   (Abstract & more)
  Abstract: Cognitive science is a form of "reverse engineering" (as Dennett has dubbed it). We are trying to explain the mind by building (or explaining the functional principles of) systems that have minds. A "Turing" hierarchy of empirical constraints can be applied to this task, from t1, toy models that capture only an arbitrary fragment of our performance capacity, to T2, the standard "pen-pal" Turing Test (total symbolic capacity), to T3, the Total Turing Test (total symbolic plus robotic capacity), to T4 (T3 plus internal [neuromolecular] indistinguishability). All scientific theories are underdetermined by data. What is the right level of empirical constraint for cognitive theory? I will argue that T2 is underconstrained (because of the Symbol Grounding Problem and Searle's Chinese Room Argument) and that T4 is overconstrained (because we don't know what neural data, if any, are relevant). T3 is the level at which we solve the "other minds" problem in everyday life, the one at which evolution operates (the Blind Watchmaker is no mind-reader either) and the one at which symbol systems can be grounded in the robotic capacity to name and manipulate the objects their symbols are about. I will illustrate this with a toy model for an important component of T3 -- categorization -- using neural nets that learn category invariance by "warping" similarity space the way it is warped in human categorical perception: within-category similarities are amplified and between-category similarities are attenuated. This analog "shape" constraint is the grounding inherited by the arbitrarily shaped symbol that names the category and by all the symbol combinations it enters into. No matter how tightly one constrains any such model, however, it will always be more underdetermined than normal scientific and engineering theory. This will remain the ineliminable legacy of the mind/body problem
• Stevan Harnad (1994). Levels of functional equivalence in reverse bioengineering: The Darwinian Turing test for artificial life.   (Abstract & more)
  Abstract: Both Artificial Life and Artificial Mind are branches of what Dennett has called "reverse engineering": Ordinary engineering attempts to build systems to meet certain functional specifications, reverse bioengineering attempts to understand how systems that have already been built by the Blind Watchmaker work. Computational modelling (virtual life) can capture the formal principles of life, perhaps predict and explain it completely, but it can no more be alive than a virtual forest fire can be hot. In itself, a computational model is just an ungrounded symbol system; no matter how closely it matches the properties of what is being modelled, it matches them only formally, with the mediation of an interpretation. Synthetic life is not open to this objection, but it is still an open question how close a functional equivalence is needed in order to capture life. Close enough to fool the Blind Watchmaker is probably close enough, but would that require molecular indistinguishability, and if so, do we really need to go that far?
  Additional links for this entry:
  http://eprints.resist.ecs.soton.ac.uk/3363/
  http://portal.acm.org/citation.cfm?id=188445
  http://cogprints.org/1591/00/harnad94.artlife2.html
  http://cogprints.soton.ac.uk/documents/disk0/00/00/15/91/
  http://mitpress.mit.edu/catalog/item/default.asp?ttype=6&tid=40
  http://cogsci.soton.ac.uk/~harnad/Papers/Harnad/harnad94.artlife2.html
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad94.artlife2.html
  http://eprints.ecs.soton.ac.uk/archive/00003363/02/harnad94.artlife2.html
  http://cogprints.ecs.soton.ac.uk/archive/00001591/00/harnad94.artlife2.html
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:1591
  
• Stevan Harnad (1991). Other bodies, other minds: A machine incarnation of an old philosophical problem.   (Abstract & more)
  Abstract:   Any attempt to explain the mind by building machines with minds must confront the other-minds problem: How can we tell whether any body other than our own has a mind when the only way to know is by being the other body? In practice we all use some form of Turing Test: If it can do everything a body with a mind can do such that we can't tell them apart, we have no basis for doubting it has a mind. But what is everything a body with a mind can do? Turing's original pen-pal version of the Turing Test (the TT) only tested linguistic capacity, but Searle has shown that a mindless symbol-manipulator could pass the TT undetected. The Total Turing Test (TTT) calls instead for all of our linguistic and robotic capacities; immune to Searle's argument, it suggests how to ground a symbol manipulating system in the capacity to pick out the objects its symbols refer to. No Turing Test, however, can guarantee that a body has a mind. Worse, nothing in the explanation of its successful performance requires a model to have a mind at all. Minds are hence very different from the unobservables of physics (e.g., superstrings); and Turing Testing, though essential for machine-modeling the mind, can really only yield an explanation of the body
  Additional links for this entry:
  http://eprints.ecs.soton.ac.uk/archive/00003379/
  http://cogprints.ecs.soton.ac.uk/archive/00001578/
  http://portal.acm.org/citation.cfm?id=103493.103530
  http://cogprints.org/1578/0/harnad91.otherminds.html
  http://cogprints.org/1578/00/harnad91.otherminds.html
  http://cogprints.soton.ac.uk/documents/disk0/00/00/15/78/
  http://eprints.ecs.soton.ac.uk/archive/00003379/01/harnad91.otherminds.html
  http://cogprints.ecs.soton.ac.uk/archive/00001578/00/harnad91.otherminds.html
  http://citebase.eprints.org/cgi-bin/citations?id=oai:eprints.ecs.soton.ac.uk:3379
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:1578
  http://www.springerlink.com/content/t5733025r3t44248/fulltext.pdf
  http://www.springerlink.com/index/T5733025R3T44248.pdf
  
• Stevan Harnad (2004). The Annotation Game: On Turing (1950) on Computing, Machinery, and Intelligence.   (Abstract & more)
  Abstract: This quote/commented critique of Turing's classical paper suggests that Turing meant -- or should have meant -- the robotic version of the Turing Test (and not just the email version). Moreover, any dynamic system (that we design and understand) can be a candidate, not just a computational one. Turing also dismisses the other-minds problem and the mind/body problem too quickly. They are at the heart of both the problem he is addressing and the solution he is proposing
  Additional links for this entry:
  http://eprints.ecs.soton.ac.uk/12954/
  http://cogprints.org/3322/02/turing.pdf
  http://cogprints.org/3322/01/turing.html
  http://eprints.resist.ecs.soton.ac.uk/7741/
  http://cogprints.ecs.soton.ac.uk/archive/00003322/
  http://www.ecs.soton.ac.uk/~harnad/Temp/turing.doc
  http://www.ecs.soton.ac.uk/~harnad/Temp/turing.html
  http://eprints.ecs.soton.ac.uk/archive/00007741/01/turing.html
  http://cogprints.ecs.soton.ac.uk/archive/00003322/01/turing.html
  http://citebase.eprints.org/cgi-bin/citations?id=oai:eprints.ecs.soton.ac.uk:7741
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:eprints.ecs.soton.ac.uk:7741
  
• Stevan Harnad (2006). The annotation game: On Turing (1950) on computing, machinery, and intelligence.   (Abstract & more)
  Abstract: This quote/commented critique of Turing's classical paper suggests that Turing meant -- or should have meant -- the robotic version of the Turing Test (and not just the email version). Moreover, any dynamic system (that we design and understand) can be a candidate, not just a computational one. Turing also dismisses the other-minds problem and the mind/body problem too quickly. They are at the heart of both the problem he is addressing and the solution he is proposing
  Additional links for this entry:
  http://eprints.ecs.soton.ac.uk/12954/
  http://cogprints.org/3322/1/turing.html
  http://cogprints.org/3322/02/turing.pdf
  http://cogprints.org/3322/01/turing.html
  http://eprints.resist.ecs.soton.ac.uk/7741/
  http://cogprints.ecs.soton.ac.uk/archive/00003322/
  http://www.ecs.soton.ac.uk/~harnad/Temp/turing.doc
  http://www.ecs.soton.ac.uk/~harnad/Temp/turing.html
  http://eprints.ecs.soton.ac.uk/archive/00007741/01/turing.html
  http://cogprints.ecs.soton.ac.uk/archive/00003322/01/turing.html
  http://citebase.eprints.org/cgi-bin/citations?id=oai:eprints.ecs.soton.ac.uk:7741
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:eprints.ecs.soton.ac.uk:7741
  
• Stevan Harnad (1992). The Turing test is not a trick.   (Abstract & more)
  Abstract: It is important to understand that the Turing Test (TT) is not, nor was it intended to be, a trick; how well one can fool someone is not a measure of scientific progress. The TT is an empirical criterion: It sets AI's empirical goal to be to generate human-scale performance capacity. This goal will be met when the candidate's performance is totally indistinguishable from a human's. Until then, the TT simply represents what it is that AI must endeavor eventually to accomplish scientifically
  Additional links for this entry:
  http://eprints.resist.ecs.soton.ac.uk/3373/
  http://cogprints.org/1584/00/harnad92.turing.html
  http://portal.acm.org/citation.cfm?id=141420.141422
  http://cogprints.soton.ac.uk/documents/disk0/00/00/15/84/
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad92.turing.html
  http://citebase.eprints.org/cgi-bin/citations?id=oai:cogprints.soton.ac.uk:1584
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:1584
  http://cogprints.org/1584/0/harnad92.turing.html
  
• Larry Hauser (2001). Look who's moving the goal posts now.   (Abstract & more)
  Abstract:   The abject failure of Turing's first prediction (of computer success in playing the Imitation Game) confirms the aptness of the Imitation Game test as a test of human level intelligence. It especially belies fears that the test is too easy. At the same time, this failure disconfirms expectations that human level artificial intelligence will be forthcoming any time soon. On the other hand, the success of Turing's second prediction (that acknowledgment of computer thought processes would become commonplace) in practice amply confirms the thought that computers think in some manner and are possessed of some level of intelligence already. This lends ever-growing support to the hypothesis that computers will think at a human level eventually, despite the abject failure of Turing's first prediction
  Additional links for this entry:
  http://www.springerlink.com/content/p14045502315u372/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=319542&PDF=1
  http://www.springerlink.com/index/P14045502315U372.pdf
  http://www.ingentaconnect.com/content/klu/mind/2001/00000011/00000001/00319542
  
• Larry Hauser (1993). Reaping the whirlwind: Reply to Harnad's Other Bodies, Other Minds.   (Abstract & more)
  Abstract:   Harnad''s proposed robotic upgrade of Turing''s Test (TT), from a test of linguistic capacity alone to a Total Turing Test (TTT) of linguisticand sensorimotor capacity, conflicts with his claim that no behavioral test provides even probable warrant for attributions of thought because there is no evidence of consciousness besides private experience. Intuitive, scientific, and philosophical considerations Harnad offers in favor of his proposed upgrade are unconvincing. I agree with Harnad that distinguishing real from as if thought on the basis of (presence or lack of) consciousness (thus rejecting Turing (behavioral) testing as sufficient warrant for mental attribution)has the skeptical consequence Harnad accepts — there is in factno evidence for me that anyone else but me has a mind. I disagree with hisacceptance of it! It would be better to give up the neo-Cartesian faith in private conscious experience underlying Harnad''s allegiance to Searle''s controversial Chinese Room Experiment than give up all claim to know others think. It would be better to allow that (passing) Turing''s Test evidences — evenstrongly evidences — thought
  Additional links for this entry:
  http://members.aol.com/lshauser/harnad3.html
  http://cogprints.ecs.soton.ac.uk/archive/00000241/00/reaping.html
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:241
  http://www.springerlink.com/content/h727v843532tp041/fulltext.pdf
  http://www.springerlink.com/index/H727V843532TP041.pdf
  
• Jose Hernandez-Orallo (2000). Beyond the Turing test.   (Abstract & more)
  Abstract: The main factor of intelligence is defined as the ability tocomprehend, formalising this ability with the help of new constructsbased on descriptional complexity. The result is a comprehension test,or C-test, which is exclusively defined in computational terms. Due toits absolute and non-anthropomorphic character, it is equally applicableto both humans and non-humans. Moreover, it correlates with classicalpsychometric tests, thus establishing the first firm connection betweeninformation theoretical notions and traditional IQ tests. The TuringTest is compared with the C-test and the combination of the two isquestioned. In consequence, the idea of using the Turing Test as apractical test of intelligence should be surpassed, and substituted bycomputational and factorial tests of different cognitive abilities, amuch more useful approach for artificial intelligence progress and formany other intriguing questions that present themselves beyond theTuring Test
  Additional links for this entry:
  http://portal.acm.org/citation.cfm?id=595843.595997
  http://www.dsic.upv.es/~jorallo/escrits/TT-JHdez.ps.gz
  http://citeseer.ist.psu.edu/hernandez-orallo99beyond.html
  http://www.springerlink.com/content/h271n6173ll3773x/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=269489&PDF=1
  http://www.springerlink.com/index/H271N6173LL3773X.pdf
  http://www.ingentaconnect.com/content/klu/jlli/2000/00000009/00000004/00269489
  
• Justin Leiber (2001). Turing and the fragility and insubstantiality of evolutionary explanations: A puzzle about the unity of Alan Turing's work with some larger implications.   (Abstract & more)
  Abstract: As is well known, Alan Turing drew a line, embodied in the "Turing test," between intellectual and physical abilities, and hence between cognitive and natural sciences. Less familiarly, he proposed that one way to produce a "passer" would be to educate a "child machine," equating the experimenter's improvements in the initial structure of the child machine with genetic mutations, while supposing that the experimenter might achieve improvements more expeditiously than natural selection. On the other hand, in his foundational "On the chemical basis of morphogenesis," Turing insisted that biological explanation clearly confine itself to purely physical and chemical means, eschewing vitalist and teleological talk entirely and hewing to D'Arcy Thompson's line that "evolutionary 'explanations,'" are historical and narrative in character, employing the same intentional and teleological vocabulary we use in doing human history, and hence, while perhaps on occasion of heuristic value, are not part of biology as a natural science. To apply Turing's program to recent issues, the attempt to give foundations to the social and cognitive sciences in the "real science" of evolutionary biology (as opposed to Turing's biology) is neither to give foundations, nor to achieve the unification of the social/cognitive sciences and the natural sciences
  Additional links for this entry:
  http://www.informaworld.com/smpp/./ftinterface~content=a713690490~fulltext=713240930
  
• Justin Leiber (2006). Turing's golden: How well Turing's work stands today.   (Abstract & more)
  Abstract: A. M. Turing has bequeathed us a conceptulary including 'Turing, or Turing-Church, thesis', 'Turing machine', 'universal Turing machine', 'Turing test' and 'Turing structures', plus other unnamed achievements. These include a proof that any formal language adequate to express arithmetic contains undecidable formulas, as well as achievements in computer science, artificial intelligence, mathematics, biology, and cognitive science. Here it is argued that these achievements hang together and have prospered well in the 50 years since Turing's death
  Additional links for this entry:
  http://www.informaworld.com/smpp/./ftinterface~content=a741477282~fulltext=713240930
  http://taylorandfrancis.metapress.com/index/NGH381WR75272U7R.pdf
  http://www.informaworld.com/index/741477282.pdf
  http://www.ingentaconnect.com/content/routledg/cphp/2006/00000019/00000001/art00003
  http://www.ingentaconnect.com/content/routledg/cphp/latest
  
• Robert S. Lockhart (2000). Modularity, cognitive penetrability and the Turing test.   (Abstract & more)
  Abstract: The Turing Test blurs the distinction between a model and irrelevant) instantiation details. Modeling only functional modules is problematic if these are interconnected and cognitively penetrable
  Additional links for this entry:
  http://psycprints.ecs.soton.ac.uk/archive/00000068/
  
• Donald Michie (1993). Turing's test and conscious thought.   (More)
• P. Millar (1973). On the point of the imitation game.   (More)
  Additional links for this entry:
  http://links.jstor.org/sici?sici=0026-4423(197310)2:82:328<595:OTPOTI>2.0.CO;2-7
  http://www.jstor.org/sici?sici=0026-4423(197310)2:82:328<595:OTPOTI>2.0.CO;2-7
  http://www.jstor.org/stable/pdfplus/2252214.pdf
  
• James H. Moor (1978). Explaining computer behavior.   (More)
  Additional links for this entry:
  http://www.springerlink.com/content/x313g334823725mv/fulltext.pdf
  http://www.springerlink.com/index/X313G334823725MV.pdf
  
• James H. Moor (2001). The status and future of the Turing test.   (Abstract & more)
  Abstract:   The standard interpretation of the imitation game is defended over the rival gender interpretation though it is noted that Turing himself proposed several variations of his imitation game. The Turing test is then justified as an inductive test not as an operational definition as commonly suggested. Turing's famous prediction about his test being passed at the 70% level is disconfirmed by the results of the Loebner 2000 contest and the absence of any serious Turing test competitors from AI on the horizon. But, reports of the death of the Turing test and AI are premature. AI continues to flourish and the test continues to play an important philosophical role in AI. Intelligence attribution, methodological, and visionary arguments are given in defense of a continuing role for the Turing test. With regard to Turing's predictions one is disconfirmed, one is confirmed, but another is still outstanding
  Additional links for this entry:
  http://books.google.com/books?hl=en&lr=&id=ECj6fuEMdp0C&oi=fnd&pg=RA3-PA197&ots=blQIDolec0&sig=7Zb746qi1B6hBAlr4ehD3tEmgZc
  http://books.google.com/books?hl=en&lr=&id=5BJaXSedqfIC&oi=fnd&pg=RA3-PA197&ots=rzjaULCgnv&sig=BtFI0p2CUYyifPgOjuKkYI__bFc
  http://www.springerlink.com/content/ju585836x7571202/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=319545&PDF=1
  http://www.springerlink.com/index/JU585836X7571202.pdf
  http://www.ingentaconnect.com/content/klu/mind/2001/00000011/00000001/00319545
  
• Shaun Nichols & Stephen P. Stich (1994). Folk psychology.   (Abstract & more)
  Abstract: For the last 25 years discussions and debates about commonsense psychology (or “folk psychology,” as it is often called) have been center stage in the philosophy of mind. There have been heated disagreements both about what folk psychology is and about how it is related to the scientific understanding of the mind/brain that is emerging in psychology and the neurosciences. In this chapter we will begin by explaining why folk psychology plays such an important role in the philosophy of mind. Doing that will require a quick look at a bit of the history of philosophical discussions about the mind. We’ll then turn our attention to the lively contemporary discussions aimed at clarifying the philosophical role that folk psychology is expected to play and at using findings in the cognitive sciences to get a clearer understanding of the exact nature of folk psychology
  Additional links for this entry:
  http://www.blutner.de/philom/Texte/folkpsych5.pdf
  http://www.blutner.de/NeuralNets/Texts/folkpsych5.pdf
  http://amor.rz.hu-berlin.de/~h0998dgh/philos/Texte/folkpsych5.pdf
  http://amor.cms.hu-berlin.de/~h0998dgh/philos/Texte/folkpsych5.pdf
  http://dingo.sbs.arizona.edu/~snichols/Papers/FolkPsychologyECS.pdf
  http://amor.rz.hu-berlin.de/~h0998dgh/NeuralNets/Texts/folkpsych5.pdf
  http://www.rci.rutgers.edu/~stich/Publications/Papers/FolkPsychology.pdf
  http://www.rci.rutgers.edu/~stich/Publications/Papers/FolkPsychology.pdf
  http://www-personal.umich.edu/~lormand/phil/teach/mmm/readings/Stich - Cognitive Science and the Appeal to Tacit Theory.rtf
  http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=8039374&dopt=Citation
  
• Gualtiero Piccinini (2000). Turing's rules for the imitation game.   (Abstract & more)
  Abstract:   In the 1950s, Alan Turing proposed his influential test for machine intelligence, which involved a teletyped dialogue between a human player, a machine, and an interrogator. Two readings of Turing''s rules for the test have been given. According to the standard reading of Turing''s words, the goal of the interrogator was to discover which was the human being and which was the machine, while the goal of the machine was to be indistinguishable from a human being. According to the literal reading, the goal of the machine was to simulate a man imitating a woman, while the interrogator – unaware of the real purpose of the test – was attempting to determine which of the two contestants was the woman and which was the man. The present work offers a study of Turing''s rules for the test in the context of his advocated purpose and his other texts. The conclusion is that there are several independent and mutually reinforcing lines of evidence that support the standard reading, while fitting the literal reading in Turing''s work faces severe interpretative difficulties. So, the controversy over Turing''s rules should be settled in favor of the standard reading
  Additional links for this entry:
  http://books.google.com/books?hl=en&lr=&id=5BJaXSedqfIC&oi=fnd&pg=RA1-PA573&ots=rzj9ZTxlot&sig=sOABQfQAHOiAecLsjc4Dkdn0Kko
  http://books.google.com/books?hl=en&lr=&id=ECj6fuEMdp0C&oi=fnd&pg=RA1-PA573&ots=blQHIwgjd_&sig=k_FvcCrJGK1pHaGSeZX1ciLb8SM
  http://www.springerlink.com/content/content/v1k277193084750u/fulltext.pdf
  http://www.springerlink.com/content/v1k277193084750u/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=319535&PDF=1
  http://www.springerlink.com/index/V1K277193084750U.pdf
  http://www.ingentaconnect.com/content/klu/mind/2000/00000010/00000004/00319535
  
• William J. Rapaport (2000). How to pass a Turing test: Syntactic semantics, natural-language understanding, and first-person cognition.   (More)
  Additional links for this entry:
  http://www.cse.buffalo.edu/tech-reports/99-06.ps
  http://www.cse.buffalo.edu/tech-reports/99-06.ps.Z
  http://www.cse.buffalo.edu/~rapaport/Papers/turing.pdf
  http://historical.ncstrl.org/litesite-data/suny_buffalo_cs/99-06.ps
  http://www.kluweronline.com/article.asp?PIPS=269490&PDF=1
  http://www.springerlink.com/index/JW2371N7T37H2V10.pdf
  http://www.ingentaconnect.com/content/klu/jlli/2000/00000009/00000004/00269490
  
• William J. Rapaport (online). Review of The Turing Test: Verbal Behavior As the Hallmark of Intelligence.   (Abstract & more)
  Abstract: Stuart M. Shieber’s name is well known to computational linguists for his research and to computer scientists more generally for his debate on the Loebner Turing Test competition, which appeared a decade earlier in Communications of the ACM (Shieber 1994a, 1994b; Loebner 1994).¹ With this collection, I expect it to become equally well known to philosophers
  Additional links for this entry:
  http://www.mitpressjournals.org/doi/pdf/10.1162/089120105774321127
  http://www.cse.buffalo.edu/~rapaport/Papers/shieberreview-original.pdf
  
• Ian Ravenscroft (online). Folk psychology as a theory.   (Abstract & more)
  Abstract: Many philosophers and cognitive scientists claim that our everyday or "folk" understanding of mental states constitutes a theory of mind. That theory is widely called "folk psychology" (sometimes "commonsense" psychology). The terms in which folk psychology is couched are the familiar ones of "belief" and "desire", "hunger", "pain" and so forth. According to many theorists, folk psychology plays a central role in our capacity to predict and explain the behavior of ourselves and others. However, the nature and status of folk psychology remains controversial
  Additional links for this entry:
  http://plato.stanford.edu/entries/folkpsych-theory
  http://plato.stanford.edu/entries/folkpsych-theory/
  http://www.seop.leeds.ac.uk/entries/folkpsych-theory/
  http://www.illc.uva.nl/~seop/entries/folkpsych-theory/
  http://www.science.uva.nl/~seop/entries/folkpsych-theory/
  http://setis.library.usyd.edu.au/stanford/entries/folkpsych-theory/
  
• Geoffrey Sampson (1973). In defence of Turing.   (More)
  Additional links for this entry:
  http://links.jstor.org/sici?sici=0026-4423(197310)2:82:328<592:IDOT>2.0.CO;2-M
  http://www.jstor.org/sici?sici=0026-4423(197310)2:82:328<592:IDOT>2.0.CO;2-M
  http://www.jstor.org/stable/pdfplus/2252213.pdf
  
• Y. Sato & T. Ikegami (2004). Undecidability in the imitation game.   (Abstract & more)
  Abstract:   This paper considers undecidability in the imitation game, the so-called Turing Test. In the Turing Test, a human, a machine, and an interrogator are the players of the game. In our model of the Turing Test, the machine and the interrogator are formalized as Turing machines, allowing us to derive several impossibility results concerning the capabilities of the interrogator. The key issue is that the validity of the Turing test is not attributed to the capability of human or machine, but rather to the capability of the interrogator. In particular, it is shown that no Turing machine can be a perfect interrogator. We also discuss meta-imitation game and imitation game with analog interfaces where both the imitator and the interrogator are mimicked by continuous dynamical systems
  Additional links for this entry:
  http://portal.acm.org/citation.cfm?id=976736
  http://www.bdc.brain.riken.jp/publications/internal/jour-Undecidability_in_the_Imitation_Game/uig.pdf
  http://www.bdc.brain.riken.go.jp/publications/internal/jour-Undecidability_in_the_Imitation_Game/uig.pdf
  http://www.bdc.brain.riken.go.jp/publications/internal/trep-Undecidability_in_the_imitation_game/riken-bsi-bdc-tr2001-04.ps.Z
  http://www.springerlink.com/content/t2771g8512m67737/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=5253133&PDF=1
  http://www.springerlink.com/index/T2771G8512M67737.pdf
  http://www.ingentaconnect.com/content/klu/mind/2004/00000014/00000002/05253133
  
• Ayse P. Saygin, Ilyas Cicekli & Varol Akman (2000). Turing test: 50 years later.   (Abstract & more)
  Abstract:   The Turing Test is one of the most disputed topics in artificial intelligence, philosophy of mind, and cognitive science. This paper is a review of the past 50 years of the Turing Test. Philosophical debates, practical developments and repercussions in related disciplines are all covered. We discuss Turing''s ideas in detail and present the important comments that have been made on them. Within this context, behaviorism, consciousness, the `other minds'' problem, and similar topics in philosophy of mind are discussed. We also cover the sociological and psychological aspects of the Turing Test. Finally, we look at the current situation and analyze programs that have been developed with the aim of passing the Turing Test. We conclude that the Turing Test has been, and will continue to be, an influential and controversial topic
  Additional links for this entry:
  http://cogprints.org/1925/0/tt50.ps
  http://cogprints.org/1925/00/tt50.ps
  http://citeseer.ist.psu.edu/378189.html
  http://crl.ucsd.edu/~saygin/papers/MMTT.pdf
  http://portal.acm.org/citation.cfm?id=596724.596952
  http://cogprints.ecs.soton.ac.uk/archive/00001925/00/tt50.ps
  http://www.cs.bilkent.edu.tr/~akman/jour-papers/mam/mam2000.pdf
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:1925
  http://www.springerlink.com/content/content/ph7275k8w0137245/fulltext.pdf
  http://www.springerlink.com/content/ph7275k8w0137245/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=319526&PDF=1
  http://www.springerlink.com/index/PH7275K8W0137245.pdf
  
• A. P. Saygin & I. Cicekli (2000). Turing test: 50 years later.   (Abstract & more)
  Abstract: The Turing Test is one of the most disputed topics in artificial intelligence, philosophy of mind, and cognitive science. This paper is a review of the past 50 years of the Turing Test. Philo- sophical debates, practical developments and repercussions in related disciplines are all covered. We discuss Turing’s ideas in detail and present the important comments that have been made on them. Within this context, behaviorism, consciousness, the ‘other minds’ problem, and similar topics in philosophy of mind are discussed. We also cover the sociological and psychological aspects of the Turing Test. Finally, we look at the current situation and analyze programs that have been developed with the aim of passing the Turing Test. We conclude that the Turing Test has been, and will continue to be, an influential and controversial topic
  Additional links for this entry:
  http://cogprints.org/1925/00/tt50.ps
  http://citeseer.ist.psu.edu/378189.html
  http://crl.ucsd.edu/~saygin/papers/MMTT.pdf
  http://portal.acm.org/citation.cfm?id=596724.596952
  http://cogprints.ecs.soton.ac.uk/archive/00001925/00/tt50.ps
  http://www.cs.bilkent.edu.tr/~akman/jour-papers/mam/mam2000.pdf
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:1925
  http://www.kluweronline.com/article.asp?PIPS=319526&PDF=1
  http://www.springerlink.com/index/PH7275K8W0137245.pdf
  
• Paul Schweizer (1998). The truly total Turing test.   (Abstract & more)
  Abstract:   The paper examines the nature of the behavioral evidence underlying attributions of intelligence in the case of human beings, and how this might be extended to other kinds of cognitive system, in the spirit of the original Turing Test (TT). I consider Harnad's Total Turing Test (TTT), which involves successful performance of both linguistic and robotic behavior, and which is often thought to incorporate the very same range of empirical data that is available in the human case. However, I argue that the TTT is still too weak, because it only tests the capabilities of particular tokens within a preexisting context of intelligent behavior. What is needed is a test of the cognitive type, as manifested through a number of exemplary tokens, in order to confirm that the cognitive type is able to produce the context of intelligent behavior presupposed by tests such as the TT and TTT
  Additional links for this entry:
  http://www.csa.com/partners/viewrecord.php?requester=gs&collection=TRD&recid=371134CI
  http://www.springerlink.com/content/h51pp233m1h732p0/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=150465&PDF=1
  http://www.springerlink.com/index/H51PP233M1H732P0.pdf
  http://www.ingentaconnect.com/content/klu/mind/1998/00000008/00000002/00150465
  
• James F. Sennett (ms). The ice man cometh: Lt. comander data and the Turing test.   (More)
• Stuart M. Shieber (1994). Lessons from a restricted Turing test.   (More)
  Additional links for this entry:
  http://adsabs.harvard.edu/abs/1994cmp.lg....4002S
  http://citeseer.ist.psu.edu/shieber93lessons.html
  http://www.eecs.harvard.edu/shieber/Biblio/Papers/loebner-rev-html/loebner-rev-html.html
  http://www.eecs.harvard.edu/~shieber/Biblio/Papers/loebner-rev-html/loebner-rev-html.html
  http://portal.acm.org/citation.cfm?id=175208.175217&dl=GUIDE&dl=ACM&idx=175208&part=periodical&WantType=periodical&title=Communications of the ACM
  
• Susan G. Sterrett (2002). Nested algorithms and the original imitation game test: A reply to James Moor.   (More)
  Additional links for this entry:
  http://www.springerlink.com/content/x4225320762736q0/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=391369&PDF=1
  http://www.springerlink.com/index/X4225320762736Q0.pdf
  http://www.ingentaconnect.com/content/klu/mind/2002/00000012/00000001/00391369
  
• Susan G. Sterrett (2000). Turing's two tests for intelligence.   (Abstract & more)
  Abstract:   On a literal reading of `Computing Machinery and Intelligence'', Alan Turing presented not one, but two, practical tests to replace the question `Can machines think?'' He presented them as equivalent. I show here that the first test described in that much-discussed paper is in fact not equivalent to the second one, which has since become known as `the Turing Test''. The two tests can yield different results; it is the first, neglected test that provides the more appropriate indication of intelligence. This is because the features of intelligence upon which it relies are resourcefulness and a critical attitude to one''s habitual responses; thus the test''s applicablity is not restricted to any particular species, nor does it presume any particular capacities. This is more appropriate because the question under consideration is what would count as machine intelligence. The first test realizes a possibility that philosophers have overlooked: a test that uses a human''s linguistic performance in setting an empirical test of intelligence, but does not make behavioral similarity to that performance the criterion of intelligence. Consequently, the first test is immune to many of the philosophical criticisms on the basis of which the (so-called) `Turing Test'' has been dismissed
  Additional links for this entry:
  http://books.google.com/books?hl=en&lr=&id=ECj6fuEMdp0C&oi=fnd&pg=RA1-PA519&ots=blQIDonh93&sig=kpE5iqY7Fjm67XjSS7t2e9XqGDo
  http://www.springerlink.com/content/content/k11t54j7821h4230/fulltext.pdf
  http://www.springerlink.com/content/k11t54j7821h4230/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=319533&PDF=1
  http://www.springerlink.com/index/K11T54J7821H4230.pdf
  http://www.ingentaconnect.com/content/klu/mind/2000/00000010/00000004/00319533
  
• Saul Traiger (2000). Making the right identification in the Turing test.   (Abstract & more)
  Abstract:   The test Turing proposed for machine intelligence is usually understood to be a test of whether a computer can fool a human into thinking that the computer is a human. This standard interpretation is rejected in favor of a test based on the Imitation Game introduced by Turing at the beginning of "Computing Machinery and Intelligence."
  Additional links for this entry:
  http://www.traiger.oxy.edu/publications/making-the-right-identification.pdf
  http://faculty.oxy.edu/traiger/publications/making-the-right-identification.pdf
  http://0-www.faculty.oxy.edu.oasys.lib.oxy.edu/traiger/publications/making-the-right-identification.pdf
  http://books.google.com/books?hl=en&lr=&id=5BJaXSedqfIC&oi=fnd&pg=RA1-PA561&ots=rzjaULFcit&sig=SFxczaJwBF-Ba70js7yMbXB8L6Y
  http://books.google.com/books?hl=en&lr=&id=ECj6fuEMdp0C&oi=fnd&pg=RA1-PA561&ots=blQIDooa7_&sig=4ZGzMTB0yiYy62v_qt0Q_DwtyKI
  http://www.springerlink.com/content/g90h6kqu506lwr75/fulltext.pdf
  http://www.springerlink.com/index/G90H6KQU506LWR75.pdf
  http://www.ingentaconnect.com/content/klu/mind/2000/00000010/00000004/00319538
  
• Peter Turney (2001). Answering subcognitive Turing test questions: A reply to French.   (Abstract & more)
  Abstract: Robert French has argued that a disembodied computer is incapable of passing a Turing Test that includes subcognitive questions. Subcognitive questions are designed to probe the network of cultural and perceptual associations that humans naturally develop as we live, embodied and embedded in the world. In this paper, I show how it is possible for a disembodied computer to answer subcognitive questions appropriately, contrary to French's claim. My approach to answering subcognitive questions is to use statistical information extracted from a very large collection of text. In particular, I show how it is possible to answer a sample of subcognitive questions taken from French, by issuing queries to a search engine that indexes about 350 million Web pages. This simple algorithm may shed light on the nature of human (sub-) cognition, but the scope of this paper is limited to demonstrating that French is mistaken: a disembodied computer can answer subcognitive questions
  Additional links for this entry:
  http://cogprints.org/1798/01/subcognitive.ps
  http://cogprints.org/1798/0/subcognitive.pdf
  http://cogprints.org/1798/00/subcognitive.pdf
  http://adsabs.harvard.edu/abs/2002cs.......12015T
  http://citeseer.ist.psu.edu/turney01answering.html
  http://cogprints.ecs.soton.ac.uk/archive/00001798/
  http://www.extractor.com/download/documents/subcognitive.pdf
  http://cogprints.ecs.soton.ac.uk/archive/00001798/00/subcognitive.pdf
  https://iit-iti.nrc-cnrc.gc.ca/iit-publications-iti/docs/NRC-44898.pdf
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:1798
  http://www.phil.canterbury.ac.nz/tom_bestor/e-texts/Turney - Answering subcognitive questions Reply to French NRC-44898.pdf
  http://taylorandfrancis.metapress.com/index/TW3Q03K8NK7UVQJG.pdf
  http://www.informaworld.com/index/TW3Q03K8NK7UVQJG.pdf
  http://www.ingentaconnect.com/content/tandf/teta/2001/00000013/00000004/art00006
  
• Alan M. Turing (1950). Computing machinery and intelligence.   (Abstract & more)
  Abstract: I propose to consider the question, "Can machines think?" This should begin with definitions of the meaning of the terms "machine" and "think." The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous, If the meaning of the words "machine" and "think" are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to the question, "Can machines think?" is to be sought in a statistical survey such as a Gallup poll. But this is absurd. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words. The new form of the problem can be described in terms of a game which we call the 'imitation game." It is played with three people, a man (A), a woman (B), and an interrogator (C) who may be of either sex. The interrogator stays in a room apart front the other two. The object of the game for the interrogator is to determine which of the other two is the man and which is the woman. He knows them by labels X and Y, and at the end of the game he says either "X is A and Y is B" or "X is B and Y is A." The interrogator is allowed to put questions to A and B. We now ask the question, "What will happen when a machine takes the part of A in this game?" Will the interrogator decide wrongly as often when the game is played like this as he does when the game is played between a man and a woman? These questions replace our original, "Can machines think?"
  Additional links for this entry:
  http://cogprints.org/499/0/turing.html
  http://www.ttt.org/ling490/TuringTest.pdf
  http://www.agent.ai/doc/upload/200302/turi50_1.pdf
  http://eric.ed.gov/ERICWebPortal/recordDetail?accno=EJ216711
  http://www.dcs.gla.ac.uk/~joe/Teaching/ATiCS/FC-TuringAI-intro.pdf
  http://www.dfki.uni-sb.de/imedia/lidos/bibtex/Collins_a10168-96.html
  http://www.marxists.org/reference/subject/philosophy/works/en/turing.htm
  http://lia.deis.unibo.it/corsi/2005-2006/SID-LS-CE/downloads/turing-article.pdf
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:499
  http://twiki.di.uniroma1.it/twiki/viewfile/Users/MarcoBianchi?rev=1.1;filename=TuringComputingMachineryAndIntelligence.pdf
  http://archive.computerhistory.org/projects/chess/related_materials/text/2-0 and 2-1.Computing_machinery_and_intelligence.turing/2-0 and 2-1.Computing_machinery_and_intelligence.turing-alan.mind-59.1950.062303001.pdf
  http://links.jstor.org/sici?sici=0026-4423(195010)2:59:236<433:CMAI>2.0.CO;2-5
  http://www.jstor.org/sici?sici=0026-4423(195010)2:59:236<433:CMAI>2.0.CO;2-5
  http://mind.oxfordjournals.org/cgi/reprint/LIX/236/433
  http://www.jstor.org/stable/pdfplus/2251299.pdf
  
• S. Watt (1996). Naive psychology and the inverted Turing test.   (Abstract & more)
  Abstract: This target article argues that the Turing test implicitly rests on a "naive psychology," a naturally evolved psychological faculty which is used to predict and understand the behaviour of others in complex societies. This natural faculty is an important and implicit bias in the observer's tendency to ascribe mentality to the system in the test. The paper analyses the effects of this naive psychology on the Turing test, both from the side of the system and the side of the observer, and then proposes and justifies an inverted version of the test which allows the processes of ascription to be analysed more directly than in the standard version
  Additional links for this entry:
  http://citeseer.ist.psu.edu/watt96naive.html
  http://psycprints.ecs.soton.ac.uk/archive/00000506/
  http://psycprints.ecs.soton.ac.uk/perl/local/psyc/makedoc?id=506&type=html
  http://psycprints.ecs.soton.ac.uk/archive/00000506/02/psyc.96.7.14.turing-test.1.watt
  http://psycprints.ecs.soton.ac.uk/archive/00000506/01/psyc.96.7.14.turing-test.1.watt.xml
  
• Blay Whitby (1996). Why the Turing test is ai's biggest blind Alley.   (More)
• Sean Zdenek (2001). Passing loebner's Turing test: A case of conflicting discourse functions.   (Abstract & more)
  Abstract:   This paper argues that the Turing test is based on a fixed and de-contextualized view of communicative competence. According to this view, a machine that passes the test will be able to communicate effectively in a variety of other situations. But the de-contextualized view ignores the relationship between language and social context, or, to put it another way, the extent to which speakers respond dynamically to variations in discourse function, formality level, social distance/solidarity among participants, and participants' relative degrees of power and status (Holmes, 1992). In the case of the Loebner Contest, a present day version of the Turing test, the social context of interaction can be interpreted in conflicting ways. For example, Loebner discourse is defined 1) as a friendly, casual conversation between two strangers of equal power, and 2) as a one-way transaction in which judges control the conversational floor in an attempt to expose contestants that are not human. This conflict in discourse function is irrelevant so long as the goal of the contest is to ensure that only thinking, human entities pass the test. But if the function of Loebner discourse is to encourage the production of software that can pass for human on the level of conversational ability, then the contest designers need to resolve this ambiguity in discourse function, and thus also come to terms with the kind of competence they are trying to measure
  Additional links for this entry:
  http://books.google.com/books?hl=en&lr=&id=5BJaXSedqfIC&oi=fnd&pg=RA2-PA53&ots=rzjaULFlks&sig=a-VgtvUjcFyxiSpkIASbwHF4Imk
  http://books.google.com/books?hl=en&lr=&id=ECj6fuEMdp0C&oi=fnd&pg=RA1-PA583&ots=blQIDooj9Z&sig=IxxOEy4OGv0MfwNy7oTRa0j0_9g
  http://www.springerlink.com/content/p1572g5485036674/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=319544&PDF=1
  http://www.springerlink.com/index/P1572G5485036674.pdf
  http://www.ingentaconnect.com/content/klu/mind/2001/00000011/00000001/00319544
  

Godelian arguments

• Damjan Bojadziev (1997). Mind versus Godel.   (More)
  Additional links for this entry:
  http://books.google.com/books?hl=en&lr=&id=VHZy4j_Qa-cC&oi=fnd&pg=PA202&dq=+Mind+versus+Godel+Bojadziev&ots=RjBGkflpmk&sig=oyuz5heebVFZdtmfGXFv50bP2zo
  
• Selmer Bringsjord & H. Xiao (2000). A refutation of Penrose's new Godelian case against the computational conception of mind.   (More)
• David J. Chalmers (1996). Minds, machines, and mathematics.   (Abstract & more)
  Abstract: In his stimulating book SHADOWS OF THE MIND, Roger Penrose presents arguments, based on Gödel's theorem, for the conclusion that human thought is uncomputable. There are actually two separate arguments in Penrose's book. The second has been widely ignored, but seems to me to be much more interesting and novel than the first. I will address both forms of the argument in some detail. Toward the end, I will also comment on Penrose's proposals for a "new science of consciousness"
  Additional links for this entry:
  http://www.u.arizona.edu/~chalmers/papers/penrose.html
  http://psyche.cs.monash.edu.au/v2/psyche-2-09-chalmers.html
  http://calculemus.org/MathUniversalis/NS/10/03chalmers.html
  http://psyche.cs.monash.edu.au/volume2-1/psyche-95-2-09-shadows-7-chalmers.html
  
• Jack Copeland (1998). Turing's o-machines, Searle, Penrose, and the brain.   (Abstract & more)
  Abstract: In his PhD thesis (1938) Turing introduced what he described as 'a new kind of machine'. He called these 'O-machines'. The present paper employs Turing's concept against a number of currently fashionable positions in the philosophy of mind
  Additional links for this entry:
  http://www.phil.canterbury.ac.nz/jack_copeland/pub/turing1.pdf
  http://www.alanturing.net/turing_archive/pages/pub/turing1/turing1.pdf
  http://www.phil.canterbury.ac.nz/personal_pages/jack_copeland/pub/turing1.pdf
  http://www.phil.canterbury.ac.nz/tom_bestor/e-texts/Copeland, Jack - Turing's O-Machines, Penrose, Searle and the Brain turing-s-o-machines.pdf
  http://www.blackwell-synergy.com/links/doi/10.1111/1467-8284.00113
  http://www.blackwell-synergy.com/doi/abs/10.1111/1467-8284.00113
  http://www.ingentaconnect.com/content/bpl/anal/1998/00000058/00000258/art00113
  
• Daniel C. Dennett (1989). Murmurs in the cathedral: Review of R. Penrose, The Emperor's New Mind.   (Abstract & more)
  Abstract: The idea that a computer could be conscious--or equivalently, that human consciousness is the effect of some complex computation mechanically performed by our brains--strikes some scientists and philosophers as a beautiful idea. They find it initially surprising and unsettling, as all beautiful ideas are, but the inevitable culmination of the scientific advances that have gradually demystified and unified the material world. The ideologues of Artificial Intelligence (AI) have been its most articulate supporters. To others, this idea is deeply repellent: philistine, reductionistic (in some bad sense), as incredible as it is offensive. John Searle's attack on "strong AI" is the best known expression of this view, but others in the same camp, liking Searle's destination better than his route, would dearly love to see a principled, scientific argument showing that strong AI is impossible. Roger Penrose has set out to provide just such an argument
• S. Feferman (1996). Penrose's Godelian argument.   (Abstract & more)
  Abstract: In his book Shadows of the Mind: A search for the missing science of con- sciousness [SM below], Roger Penrose has turned in another bravura perfor- mance, the kind we have come to expect ever since The Emperor’s New Mind [ENM ] appeared. In the service of advancing his deep convictions and daring conjectures about the nature of human thought and consciousness, Penrose has once more drawn a wide swath through such topics as logic, computa- tion, artificial intelligence, quantum physics and the neuro-physiology of the brain, and has produced along the way many gems of exposition of difficult mathematical and scientific ideas, without condescension, yet which should be broadly appealing.¹ While the aims and a number of the topics in SM are the same as in ENM , the focus now is much more on the two axes that Pen- rose grinds in earnest. Namely, in the first part of SM he argues anew and at great length against computational models of the mind and more specifi- cally against any account of mathematical thought in computational terms. Then in the second part, he argues that there must be a scientific account of consciousness but that will require a (still to be found) non-computational extension or modification of present-day quantum physics
• H. Gaifman (2000). What Godel's incompleteness result does and does not show.   (Abstract & more)
  Abstract: In a recent paper S. McCall adds another link to a chain of attempts to enlist Gödel’s incompleteness result as an argument for the thesis that human reasoning cannot be construed as being carried out by a computer.1 McCall’s paper is undermined by a technical oversight. My concern however is not with the technical point. The argument from Gödel’s result to the no-computer thesis can be made without following McCall’s route; it is then straighter and more forceful. Yet the argument fails in an interesting and revealing way. And it leaves a remainder: if some computer does in fact simulate all our mathematical reasoning, then, in principle, we cannot fully grasp how it works. Gödel’s result also points out a certain essential limitation of self-reflection. The resulting picture parallels, not accidentally, Davidson’s view of psychology, as a science that in principle must remain “imprecise”, not fully spelt out. What is intended here by “fully grasp”, and how all this is related to self-reflection, will become clear at the end of this comment
  Additional links for this entry:
  http://links.jstor.org/sici?sici=0022-362X(200008)97:8<462:WGIRDA>2.0.CO;2-N
  http://www.jstor.org/sici?sici=0022-362X(200008)97:8<462:WGIRDA>2.0.CO;2-N
  http://www.jstor.org/stable/pdfplus/2678427.pdf
  
• Robert M. Gordon (online). Folk Psychology As Mental Simulation.   (Abstract & more)
  Abstract: by, or is otherwise relevant to the seminar "Folk Psychology vs. Mental Simulation: How Minds Understand Minds," a National
• Rick Grush & P. Churchland (1995). Gaps in Penrose's toiling.   (Abstract & more)
  Abstract: Using the Gödel Incompleteness Result for leverage, Roger Penrose has argued that the mechanism for consciousness involves quantum gravitational phenomena, acting through microtubules in neurons. We show that this hypothesis is implausible. First, the Gödel Result does not imply that human thought is in fact non algorithmic. Second, whether or not non algorithmic quantum gravitational phenomena actually exist, and if they did how that could conceivably implicate microtubules, and if microtubules were involved, how that could conceivably implicate consciousness, is entirely speculative. Third, cytoplasmic ions such as calcium and sodium are almost certainly present in the microtubule pore, barring the quantum mechanical effects Penrose envisages. Finally, physiological evidence indicates that consciousness does not directly depend on microtubule properties in any case, rendering doubtful any theory according to which consciousness is generated in the microtubules
  Additional links for this entry:
  http://mind.ucsd.edu/papers/penrose/penrose.rtf
  
• Jeffrey Ketland & Panu Raatikainen (online). Truth and provability again.   (More)
• Geoffrey Laforte, Pat Hayes & Kenneth M. Ford (1998). Why Godel's theorem cannot refute computationalism: A reply to Penrose.   (More)
• Alan M. Leslie, Shaun Nichols, Stephen P. Stich & David B. Klein (1996). Varieties of off-line simulation.   (Abstract & more)
  Abstract: In the last few years, off-line simulation has become an increasingly important alternative to standard explanations in cognitive science. The contemporary debate began with Gordon (1986) and Goldman's (1989) off-line simulation account of our capacity to predict behavior. On their view, in predicting people's behavior we take our own decision making system `off line' and supply it with the `pretend' beliefs and desires of the person whose behavior we are trying to predict; we then let the decision maker reach a decision on the basis of these pretend inputs. Figure 1 offers a `boxological' version of the off-line simulation theory of behavior prediction.(1)
• John R. Lucas (1967). Human and machine logic: A rejoinder.   (Abstract & more)
  Abstract: We can imagine a human operator playing a game of one-upmanship against a programmed computer. If the program is Fn, the human operator can print the theorem Gn, which the programmed computer, or, if you prefer, the program, would never print, if it is consistent. This is true for each whole number n, but the victory is a hollow one since a second computer, loaded with program C, could put the human operator out of a job.... It is useless for the `mentalist' to argue that any given program can always be improves since the process for improving programs can presumably be programmed also; certainly this can be done if the mentalist describes how the improvement is to be made. If he does give such a description, then he has not made a case
  Additional links for this entry:
  http://www.univ.trieste.it/~etica/2003_1/6_monographica.doc
  http://links.jstor.org/sici?sici=0007-0882(196808)19:2<155:HAMLAR>2.0.CO;2-4
  http://www.jstor.org/sici?sici=0007-0882(196808)19:2<155:HAMLAR>2.0.CO;2-4
  http://bjps.oxfordjournals.org/cgi/content/citation/19/2/155
  http://www.jstor.org/stable/pdfplus/686794.pdf
  http://bjps.oxfordjournals.org/cgi/reprint/19/2/155
  
• John R. Lucas (1970). Mechanism: A rejoinder.   (More)
• John R. Lucas (1961). Minds, machines and Godel.   (Abstract & more)
  Abstract: Goedel's theorem states that in any consistent system which is strong enough to produce simple arithmetic there are formulae which cannot be proved-in-the-system, but which we can see to be true. Essentially, we consider the formula which says, in effect, "This formula is unprovable-in-the-system". If this formula were provable-in-the-system, we should have a contradiction: for if it were provablein-the-system, then it would not be unprovable-in-the-system, so that "This formula is unprovable-in-the-system" would be false: equally, if it were provable-in-the-system, then it would not be false, but would be true, since in any consistent system nothing false can be provedin-the-system, but only truths. So the formula "This formula is unprovable-in-the-system" is not provable-in-the-system, but unprovablein-the-system. Further, if the formula "This formula is unprovablein- the-system" is unprovable-in-the-system, then it is true that that formula is unprovable-in-the-system, that is, "This formula is unprovable-in-the-system" is true. Goedel's theorem must apply to cybernetical machines, because it is of the essence of being a machine, that it should be a concrete instantiation of a formal system. It follows that given any machine which is consistent and capable of doing simple arithmetic, there is a formula which it is incapable of producing as being true---i.e., the formula is unprovable-in-the-system-but which we can see to be true. It follows that no machine can be a complete or adequate model of the mind, that minds are essentially different from machines
  Additional links for this entry:
  http://links.jstor.org/sici?sici=0031-8191(196104/07)36:137<112:MMAG>2.0.CO;2-I
  
• John R. Lucas (1968). Satan stultified: A rejoinder to Paul Benacerraf.   (Abstract & more)
  Abstract: The argument is a dialectical one. It is not a direct proof that the mind is something more than a machine, but a schema of disproof for any particular version of mechanism that may be put forward. If the mechanist maintains any specific thesis, I show that [146] a contradiction ensues. But only if. It depends on the mechanist making the first move and putting forward his claim for inspection. I do not think Benacerraf has quite taken the point. He criticizes me both for "failing to notice" that my ability to show that the Gödel sentence of a formal system is true "depends very much on how he is given
• John R. Lucas (ms). The Godelian argument: Turn over the page.   (Abstract & more)
  Abstract: I have no quarrel with the first two sentences: but the third, though charitable and courteous, is quite untrue. Although there are criticisms which can be levelled against the Gödelian argument, most of the critics have not read either of my, or either of Penrose's, expositions carefully, and seek to refute arguments we never put forward, or else propose as a fatal objection one that had already been considered and countered in our expositions of the argument. Hence my title. The Gödelian Argument uses Gödel's theorem to show that minds cannot be explained in purely mechanist terms. It has been put forward, in different forms, by Gödel himself, by Penrose, and by me
• John R. Lucas (ms). The implications of Godel's theorem.   (Abstract & more)
  Abstract: In 1931 Kurt Gödel proved two theorems about the completeness and consistency of first-order arithmetic. Their implications for philosophy are profound. Many fashionable tenets are shown to be untenable: many traditional intuitions are vindicated by incontrovertible arguments
  Additional links for this entry:
  http://users.ox.ac.uk/~jrlucas/Godel/goedhand.html
  http://users.ox.ac.uk/~jrlucas/Godel/implgoed.html
  
• Tim Maudlin (1996). Between the motion and the act.   (More)
  Additional links for this entry:
  http://psyche.cs.monash.edu.au/v2/psyche-2-02-maudlin.html
  http://psyche.cs.monash.edu.au/volume2-1/psyche-95-2-02-shadows-1-maudlin.html
  
• Storrs McCall (1999). Can a Turing machine know that the Godel sentence is true?   (More)
  Additional links for this entry:
  http://links.jstor.org/sici?sici=0022-362X(199910)96:10<525:CATMKT>2.0.CO;2-2
  http://www.jstor.org/sici?sici=0022-362X(199910)96:10<525:CATMKT>2.0.CO;2-2
  http://www.jstor.org/stable/pdfplus/2564612.pdf
  
• E. Nelson (2002). Mathematics and the mind.   (More)
  Additional links for this entry:
  http://www.math.princeton.edu/~nelson/papers/tokyo.pdf
  http://www.math.princeton.edu/~nelson/papers/tokyo.ps.gz
  http://star.tau.ac.il/~eshel/Bio_complexity/Conceptual Background/Mathematics-mind.pdf
  http://books.google.com/books?hl=en&lr=&id=eRkooap_j-YC&oi=fnd&pg=PA89&ots=1D3F8NBtaN&sig=L490G6v3TwiKps8crkNSHEMZak4
  
• Roger Penrose (1996). Beyond the doubting of a shadow.   (More)
  Additional links for this entry:
  http://calculemus.org/MathUniversalis/NS/10/01penrose.html
  http://psyche.csse.monash.edu.au/v2/psyche-2-23-penrose.html
  http://psyche.cs.monash.edu.au/volume2-1/psyche-96-2-23-shadows-10-penrose.html
  
• Gualtiero Piccinini (2003). Alan Turing and the mathematical objection.   (Abstract & more)
  Abstract:   This paper concerns Alan Turing's ideas about machines, mathematical methods of proof, and intelligence. By the late 1930s, Kurt Gödel and other logicians, including Turing himself, had shown that no finite set of rules could be used to generate all true mathematical statements. Yet according to Turing, there was no upper bound to the number of mathematical truths provable by intelligent human beings, for they could invent new rules and methods of proof. So, the output of a human mathematician, for Turing, was not a computable sequence (i.e., one that could be generated by a Turing machine). Since computers only contained a finite number of instructions (or programs), one might argue, they could not reproduce human intelligence. Turing called this the ``mathematical objection'' to his view that machines can think. Logico-mathematical reasons, stemming from his own work, helped to convince Turing that it should be possible to reproduce human intelligence, and eventually compete with it, by developing the appropriate kind of digital computer. He felt it should be possible to program a computer so that it could learn or discover new rules, overcoming the limitations imposed by the incompleteness and undecidability results in the same way that human mathematicians presumably do
  Additional links for this entry:
  http://www.springerlink.com/content/ul15v486260v8q79/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=5098147&PDF=1
  http://www.springerlink.com/index/UL15V486260V8Q79.pdf
  http://www.ingentaconnect.com/content/klu/mind/2003/00000013/00000001/05098147
  
• Hilary Putnam (1985). Reflexive reflections.   (More)
  Additional links for this entry:
  http://books.google.com/books?hl=en&lr=&id=8AT_7ZEOFf4C&oi=fnd&pg=RA2-PA143&ots=2yuzpRMYBj&sig=UU2i1OXUpETqyryBJ8N290QLcJc
  http://www.springerlink.com/content/kr0702201813pk58/fulltext.pdf
  http://www.springerlink.com/index/KR0702201813PK58.pdf
  
• Panu Raatikainen (2002). McCall's Godelian argument is invalid.   (Abstract & more)
  Abstract: Storrs McCall continues the tradition of Lucas and Penrose in an attempt to refute mechanism by appealing to Gödel’s incompleteness theorem (McCall 2001). That is, McCall argues that Gödel’s theorem “reveals a sharp dividing line between human and machine thinking”. According to McCall, “[h]uman beings are familiar with the distinction between truth and theoremhood, but Turing machines cannot look beyond their own output”. However, although McCall’s argumentation is slightly more sophisticated than the earlier Gödelian anti-mechanist arguments, in the end it fails badly, as it is at odds with the logical facts
• Panu Raatikainen (2005). On the philosophical relevance of gödel's incompleteness theorems.   (Abstract & more)
  Abstract: Gödel began his 1951 Gibbs Lecture by stating: “Research in the foundations of mathematics during the past few decades has produced some results which seem to me of interest, not only in themselves, but also with regard to their implications for the traditional philosophical problems about the nature of mathematics.” (Gödel 1951) Gödel is referring here especially to his own incompleteness theorems (Gödel 1931). Gödel’s first incompleteness theorem (as improved by Rosser (1936)) says that for any consistent formalized system F, which contains elementary arithmetic, there exists a sentence GF of the language of the system which is true but unprovable in that system. Gödel’s second incompleteness theorem states that no consistent formal system can prove its own consistency
• Panu Raatikainen (2005). Truth and provability: A comment on Redhead.   (Abstract & more)
  Abstract: Michael Redhead's recent argument aiming to show that humanly certifiable truth outruns provability is critically evaluated. It is argued that the argument is at odds with logical facts and fails
  Additional links for this entry:
  http://bjps.oxfordjournals.org/cgi/content/abstract/56/3/611
  http://bjps.oxfordjournals.org/cgi/rapidpdf/axi134v1.pdf
  http://bjps.oxfordjournals.org/cgi/reprint/56/3/611
  http://www.ingentaconnect.com/content/oup/phisci/2005/00000056/00000003/art00611
  
• William E. Seager (2003). Yesterday's algorithm: Penrose and the Godel argument.   (Abstract & more)
  Abstract: Roger Penrose is justly famous for his work in physics and mathematics but he is _notorious_ for his endorsement of the Gödel argument (see his 1989, 1994, 1997). This argument, first advanced by J. R. Lucas (in 1961), attempts to show that Gödel’s (first) incompleteness theorem can be seen to reveal that the human mind transcends all algorithmic models of it¹. Penrose's version of the argument has been seen to fall victim to the original objections raised against Lucas (see Boolos (1990) and for a particularly intemperate review, Putnam (1994)). Yet I believe that more can and should be said about the argument. Only a brief review is necessary here although I wish to present the argument in a somewhat peculiar form
• Aaron Sloman (1986). The emperor's real mind.   (More)
• Tony Stone & Martin Davies (1998). Folk psychology and mental simulation.   (Abstract & more)
  Abstract: This paper is about the contemporary debate concerning folk psychology – the debate between the proponents of the theory theory of folk psychology and the friends of the simulation alternative.¹ At the outset, we need to ask: What should we mean by this term ‘folk psychology’?
  Additional links for this entry:
  http://philrsss.anu.edu.au/~mdavies/papers/simrip.pdf
  http://www.nyu.edu/gsas/dept/philo/courses/concepts/folkpsychology.html
  

The Chinese Room

• Kristin Andrews (online). On predicting behavior.   (Abstract & more)
  Abstract: I argue that the behavior of other agents is insufficiently described in current debates as a dichotomy between tacit theory (attributing beliefs and desires to predict behavior) and simulation theory (imagining what one would do in similar circumstances in order to predict behavior). I introduce two questions about the foundation and development of our ability both to attribute belief and to simulate it. I then propose that there is one additional method used to predict behavior, namely, an inductive strategy
• Hanoch Ben-Yami (1993). A note on the chinese room.   (Abstract & more)
  Abstract:   Searle's Chinese Room was supposed to prove that computers can't understand: the man in the room, following, like a computer, syntactical rules alone, though indistinguishable from a genuine Chinese speaker, doesn't understand a word. But such a room is impossible: the man won't be able to respond correctly to questions like What is the time?, even though such an ability is indispensable for a genuine Chinese speaker. Several ways to provide the room with the required ability are considered, and it is concluded that for each of these the room will have understanding. Hence, Searle's argument is invalid
  Additional links for this entry:
  http://www.springerlink.com/content/k1nx461746n57467/fulltext.pdf
  http://www.springerlink.com/index/K1NX461746N57467.pdf
  
• Selmer Bringsjord & Ron Noel (2003). Real robots and the missing thought-experiment in the chinese room dialectic.   (More)
  Additional links for this entry:
  http://kryten.mm.rpi.edu/searlebook1.pdf
  http://citeseer.ist.psu.edu/bringsjord99real.html
  http://www.phil.canterbury.ac.nz/tom_bestor/e-texts/bringjord, searlebook1.pdf
  http://www.phil.canterbury.ac.nz/tom_bestor/e-texts/Bringsjord, Real robots (2001) searlebook1.pdf
  
• Steven Ravett Brown (2000). Peirce and formalization of thought: The chinese room argument.   (Abstract & more)
  Abstract: Whether human thinking can be formalized and whether machines can think in a human sense are questions that have been addressed by both Peirce and Searle. Peirce came to roughly the same conclusion as Searle, that the digital computer would not be able to perform human thinking or possess human understanding. However, his rationale and Searle's differ on several important points. Searle approaches the problem from the standpoint of traditional analytic philosophy, where the strict separation of syntax and semantics renders understanding impossible for a purely syntactical device. Peirce disagreed with that analysis, but argued that the computer would only be able to achieve algorithmic thinking, which he considered the simplest type. Although their approaches were radically dissimilar, their conclusions were not. I will compare and analyze the arguments of both Peirce and Searle on this issue, and outline some implications of their conclusions for the field of Artificial Intelligence
  Additional links for this entry:
  http://cogprints.org/1002/0/Peirce_Paper.html
  http://cogprints.org/1002/00/Peirce_Paper.html
  http://cogprints.ecs.soton.ac.uk/archive/00001002/
  http://cogprints.soton.ac.uk/documents/disk0/00/00/10/02/
  http://cogprints.ecs.soton.ac.uk/archive/00001002/00/Peirce_Paper.html
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:1002
  
• Graham Button, Jeff Coutler & John R. E. Lee (2000). Re-entering the chinese room: A reply to Gottfried and Traiger.   (More)
  Additional links for this entry:
  http://www.kluweronline.com/article.asp?PIPS=238829&PDF=1
  http://www.springerlink.com/index/JQ41061085707655.pdf
  http://www.ingentaconnect.com/content/klu/mind/2000/00000010/00000001/00238829
  
• David J. Chalmers (1992). Subsymbolic computation and the chinese room.   (Abstract & more)
  Abstract: More than a decade ago, philosopher John Searle started a long-running controversy with his paper “Minds, Brains, and Programs” (Searle, 1980a), an attack on the ambitious claims of artificial intelligence (AI). With his now famous _Chinese Room_ argument, Searle claimed to show that despite the best efforts of AI researchers, a computer could never recreate such vital properties of human mentality as intentionality, subjectivity, and understanding. The AI research program is based on the underlying assumption that all important aspects of human cognition may in principle be captured in a computational model. This assumption stems from the belief that beyond a certain level, implementational details are irrelevant to cognition. According to this belief, neurons, and biological wetware in general, have no preferred status as the substrate for a mind. As it happens, the best examples of minds we have at present have arisen from a carbon-based substrate, but this is due to constraints of evolution and possibly historical accidents, rather than to an absolute metaphysical necessity. As a result of this belief, many cognitive scientists have chosen to focus not on the biological substrate of the mind, but instead on the abstract causal structure_ _that the mind embodies (at an appropriate level of abstraction). The view that it is abstract causal structure that is essential to mentality has been an implicit assumption of the AI research program since Turing (1950), but was first articulated explicitly, in various forms, by Putnam (1960), Armstrong (1970) and Lewis (1970), and has become known as _functionalism_. From here, it is a very short step to _computationalism_, the view that computational structure is what is important in capturing the essence of mentality. This step follows from a belief that any abstract causal structure can be captured computationally: a belief made plausible by the Church–Turing Thesis, which articulates the power
  Additional links for this entry:
  http://consc.net/papers/subsymbolic.pdf
  http://citeseer.ist.psu.edu/chalmers92subsymbolic.html
  http://www.u.arizona.edu/~chalmers/papers/subsymbolic.pdf
  
• Paul M. Churchland & Patricia S. Churchland (1990). Could a machine think?   (More)
  Additional links for this entry:
  http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=2294584&dopt=Citation
  
• David J. Cole (1991). Artificial intelligence and personal identity.   (Abstract & more)
  Abstract:   Considerations of personal identity bear on John Searle's Chinese Room argument, and on the opposed position that a computer itself could really understand a natural language. In this paper I develop the notion of a virtual person, modelled on the concept of virtual machines familiar in computer science. I show how Searle's argument, and J. Maloney's attempt to defend it, fail. I conclude that Searle is correct in holding that no digital machine could understand language, but wrong in holding that artificial minds are impossible: minds and persons are not the same as the machines, biological or electronic, that realize them
  Additional links for this entry:
  http://www.springerlink.com/content/t130331427116747/fulltext.pdf
  http://www.springerlink.com/index/T130331427116747.pdf
  
• B. Jack Copeland (1993). The curious case of the chinese gym.   (Abstract & more)
  Abstract:   Searle has recently used two adaptations of his Chinese room argument in an attack on connectionism. I show that these new forms of the argument are fallacious. First I give an exposition of and rebuttal to the original Chinese room argument, and then a brief introduction to the essentials of connectionism
  Additional links for this entry:
  http://home.swipnet.se/drofe/chincym.pdf
  http://www.phil.canterbury.ac.nz/jack_copeland/pub/chincym.pdf
  http://www.alanturing.net/turing_archive/pages/pub/chincym/chincym.pdf
  http://www.phil.canterbury.ac.nz/personal_pages/jack_copeland/pub/chincym.pdf
  http://www.phil.canterbury.ac.nz/tom_bestor/e-texts/Copeland, Jack - Curious Case of the Chinese Gym 1993 chincym.pdf
  http://www.springerlink.com/content/ut111604435042jn/fulltext.pdf
  http://www.springerlink.com/index/UT111604435042JN.pdf
  
• Dr Louis J. Cutrona, Jr (ms). Zombies in Searle's chinese room: Putting the Turing test to bed.   (Abstract & more)
  Abstract: Searle's discussions over the years 1980-2004 of the implications of his Chinese Room Gedanken experiment are frustrating because they proceed from a correct assertion: (1) Instantiating a computer program is never by itself a sufficient condition of intentionality; and an incorrect assertion: (2) The explanation of how the brain produces intentionality cannot be that it does it by instantiating a computer program. In this article, I describe how to construct a Gedanken zombie Chinese Room program that will pass the Turing test and at the same time unambiguously demonstrates the correctness of (1). I then describe how to construct a Gedanken Chinese brain program that will pass the Turing test, has a mind, and understands Chinese, thus demonstrating that (2) is incorrect. Searle's instantiation of this program can and does produce intentionality. Searle's longstanding ignorance of Chinese is simply irrelevant and always has been. I propose a truce and a plan for further exploration
  Additional links for this entry:
  http://cogprints.org/4636/01/TR-05-002.pdf
  
• Robert I. Damper (2004). The chinese room argument--dead but not yet buried.   (More)
  Additional links for this entry:
  http://eprints.resist.ecs.soton.ac.uk/9561/
  http://eprints.ecs.soton.ac.uk/9561/01/damper.pdf
  http://www.ingentaconnect.com/content/imp/jcs/2004/00000011/F0020005/art00010
  
• Michael G. Dyer (1990). Finding lost minds.   (More)
  Additional links for this entry:
  http://www.informaworld.com/index/777957611.pdf
  
• Michael G. Dyer (1990). Intentionality and computationalism: Minds, machines, Searle and Harnad.   (More)
  Additional links for this entry:
  http://www.informaworld.com/index/777957609.pdf
  
• Ruth G. Millikan (2005). Some reflections on the theory theory - simulation theory discussion.   (More)
• Simone Gozzano (1997). The chinese room argument: Consciousness and understanding.   (More)
  Additional links for this entry:
  http://books.google.com/books?hl=en&lr=&id=VHZy4j_Qa-cC&oi=fnd&pg=PA231&ots=RjBGkheslj&sig=o6qlThOEXlScQeLhIvbrclE6lQc
  
• David Harrison (1997). Connectionism hits the chinese gym.   (More)
• Stevan Harnad (1990). Lost in the hermeneutical hall of mirrors.   (Abstract & more)
  Abstract: Critique of Computationalism as merely projecting hermeneutics (i.e., meaning originating from the mind of an external interpreter) onto otherwise intrinsically meaningless symbols. Projecting an interpretation onto a symbol system results in its being reflected back, in a spuriously self-confirming way
  Additional links for this entry:
  http://cogprints.org/1577/00/harnad90.dyer.crit.html
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad90.dyer.crit.html
  
• Stevan Harnad (1989). Minds, machines and Searle.   (Abstract & more)
  Abstract: Searle's celebrated Chinese Room Argument has shaken the foundations of Artificial Intelligence. Many refutations have been attempted, but none seem convincing. This paper is an attempt to sort out explicitly the assumptions and the logical, methodological and empirical points of disagreement. Searle is shown to have underestimated some features of computer modeling, but the heart of the issue turns out to be an empirical question about the scope and limits of the purely symbolic (computational) model of the mind. Nonsymbolic modeling turns out to be immune to the Chinese Room Argument. The issues discussed include the Total Turing Test, modularity, neural modeling, robotics, causality and the symbol-grounding problem
  Additional links for this entry:
  http://cogprints.org/1573/
  http://eprints.ecs.soton.ac.uk/1891/
  http://eprints.resist.ecs.soton.ac.uk/1891/
  http://citeseer.ist.psu.edu/harnad89minds.html
  http://cogprints.org/1573/0/harnad89.searle.html
  http://cogprints.org/1573/00/harnad89.searle.html
  http://cogprints.ecs.soton.ac.uk/archive/00001573/
  http://cogprints.ecs.soton.ac.uk/archive/00001622/
  http://cogprints.soton.ac.uk/documents/disk0/00/00/15/73/
  http://cogprints.soton.ac.uk/documents/disk0/00/00/15/73/
  http://eprints.ecs.soton.ac.uk/1891/01/harnad89.searle.html
  http://eprints.ecs.soton.ac.uk/5942/01/harnad00.searle.html
  http://eprints.ecs.soton.ac.uk/1891/01/harnad89.searle.html
  http://cogsci.soton.ac.uk/harnad/Papers/Harnad/harnad89.searle.html
  http://cogsci.soton.ac.uk/harnad/Papers/Harnad/harnad89.searle.html
  http://cogsci.soton.ac.uk/~harnad/Papers/Harnad/harnad00.searle.html
  http://cogsci.soton.ac.uk/~harnad/Papers/Harnad/harnad89.searle.html
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad89.searle.html
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad00.searle.html
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad89.searle.html
  http://eprints.ecs.soton.ac.uk/archive/00005942/01/harnad00.searle.html
  http://cogprints.ecs.soton.ac.uk/archive/00001622/00/harnad00.searle.html
  http://cogprints.ecs.soton.ac.uk/archive/00001573/00/harnad89.searle.html
  http://cogprints.ecs.soton.ac.uk/archive/00001573/00/harnad89.searle.html
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:1573
  http://www.csa.com/partners/viewrecord.php?requester=gs&collection=TRD&recid=2229271CI
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:1573
  http://web.comlab.ox.ac.uk/oucl/research/areas/ieg/e-library/sources/harnad89_searle.pdf
  http://www.informaworld.com/index/777580727.pdf
  
• Stevan Harnad (2003). Minds, machines, and Searle 2: What's right and wrong about the chinese room argument.   (Abstract & more)
  Abstract: When in 1979 Zenon Pylyshyn, associate editor of Behavioral and Brain Sciences (BBS, a peer commentary journal which I edit) informed me that he had secured a paper by John Searle with the unprepossessing title of [XXXX], I cannot say that I was especially impressed; nor did a quick reading of the brief manuscript -- which seemed to be yet another tedious "Granny Objection"[1] about why/how we are not computers -- do anything to upgrade that impression
  Additional links for this entry:
  http://eprints.ecs.soton.ac.uk/5942/01/harnad00.searle.html
  http://cogsci.soton.ac.uk/~harnad/Papers/Harnad/harnad00.searle.html
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad00.searle.html
  http://eprints.ecs.soton.ac.uk/archive/00005942/01/harnad00.searle.html
  http://cogprints.ecs.soton.ac.uk/archive/00001622/00/harnad00.searle.html
  
• Stevan Harnad (2001). Rights and wrongs of Searle's chinese room argument.   (Abstract & more)
  Abstract: "in an academic generation a little overaddicted to "politesse," it may be worth saying that violent destruction is not necessarily worthless and futile. Even though it leaves doubt about the right road for London, it helps if someone rips up, however violently, a
  Additional links for this entry:
  http://eprints.ecs.soton.ac.uk/5942/01/harnad00.searle.html
  http://cogsci.soton.ac.uk/~harnad/Papers/Harnad/harnad00.searle.html
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad00.searle.html
  
• Stevan Harnad (2001). What's wrong and right about Searle's chinese room argument?   (Abstract & more)
  Abstract: Searle's Chinese Room Argument showed a fatal flaw in computationalism (the idea that mental states are just computational states) and helped usher in the era of situated robotics and symbol grounding (although Searle himself thought neuroscience was the only correct way to understand the mind)
  Additional links for this entry:
  http://cogprints.org/4023/1/searlbook.htm
  http://cogprints.org/4023/01/searlbook.htm
  http://cogprints.org/1622/0/harnad00.searle.html
  http://cogprints.org/1622/00/harnad00.searle.html
  http://cogprints.soton.ac.uk/documents/disk0/00/00/16/22/
  http://citebase.eprints.org/cgi-bin/citations?id=oai:cogprints.soton.ac.uk:1622
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:1622
  
• Larry Hauser (2003). Nixin' goes to china.   (Abstract & more)
  Abstract: The intelligent-seeming deeds of computers are what occasion philosophical debate about artificial intelligence (AI) in the first place. Since evidence of AI is not bad, arguments against seem called for. John Searle's Chinese Room Argument (1980a, 1984, 1990, 1994) is among the most famous and long-running would-be answers to the call. Surprisingly, both the original thought experiment (1980a) and Searle's later would-be formalizations of the embedding argument (1984, 1990) are quite unavailing against AI proper (claims that computers do or someday will think ). Searle lately even styles it a "misunderstanding" (1994, p. 547) to think the argument was ever so directed! The Chinese room is now advertised to target Computationalism (claims that computation is what thought essentially is ) exclusively. Despite its renown, the Chinese Room Argument is totally ineffective even against this target
• Larry Hauser (1993). Searle's Chinese Box: The Chinese Room Argument and Artificial Intelligence.   (More)
• Larry Hauser (1997). Searle's chinese box: Debunking the chinese room argument.   (Abstract & more)
  Abstract:   John Searle's Chinese room argument is perhaps the most influential andwidely cited argument against artificial intelligence (AI). Understood astargeting AI proper – claims that computers can think or do think– Searle's argument, despite its rhetorical flash, is logically andscientifically a dud. Advertised as effective against AI proper, theargument, in its main outlines, is an ignoratio elenchi. It musterspersuasive force fallaciously by indirection fostered by equivocaldeployment of the phrase "strong AI" and reinforced by equivocation on thephrase "causal powers" (at least) equal to those of brains." On a morecarefully crafted understanding – understood just to targetmetaphysical identification of thought with computation ("Functionalism"or "Computationalism") and not AI proper the argument is still unsound,though more interestingly so. It's unsound in ways difficult for high church– "someday my prince of an AI program will come" – believersin AI to acknowledge without undermining their high church beliefs. The adhominem bite of Searle's argument against the high church persuasions of somany cognitive scientists, I suggest, largely explains the undeserved reputethis really quite disreputable argument enjoys among them
  Additional links for this entry:
  http://cogprints.org/240/0/199802002.html
  http://cogprints.org/240/00/199802002.html
  http://members.aol.com/lshauser/chiboxab.html
  http://members.aol.com/lshauser2/chinabox.html
  http://members.aol.com/wutsamada/disserta.html
  http://members.aol.com/lshauser/chiboxab.html
  http://members.aol.com/wutsamada/contents.html
  http://members.aol.com/lshauser2/chinabox.html
  http://cogprints.ecs.soton.ac.uk/archive/00000240/
  http://portal.acm.org/citation.cfm?id=596705.596737
  http://cogprints.soton.ac.uk/documents/disk0/00/00/02/40/
  http://cogprints.soton.ac.uk/documents/disk0/00/00/02/40/
  http://cogprints.ecs.soton.ac.uk/archive/00000240/00/199802002.html
  http://citebase.eprints.org/cgi-bin/citations?id=oai:cogprints.soton.ac.uk:240
  http://citebase.eprints.org/cgi-bin/citations?id=oai:cogprints.soton.ac.uk:240
  http://www.csa.com/partners/viewrecord.php?requester=gs&collection=TRD&recid=322378CI
  http://www.csa.com/partners/viewrecord.php?requester=gs&collection=TRD&recid=322378CI
  http://www.springerlink.com/content/kx8r435770352167/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=120195&PDF=1
  http://www.kluweronline.com/article.asp?PIPS=120195&PDF=1
  http://www.springerlink.com/index/KX8R435770352167.pdf
  http://www.springerlink.com/index/KX8R435770352167.pdf
  http://www.ingentaconnect.com/content/klu/mind/1997/00000007/00000002/00120195
  
• Larry Hauser (online). Searle's chinese room argument.   (Abstract & more)
  Abstract: John Searle's 1980a) thought experiment and associated 1984a) argument is one of the best known and widely credited counters to claims of artificial intelligence (AI), i.e., to claims that computers _do_ or at least _can_ (roughly, someday will) think. According to Searle's original presentation, the argument is based on two truths: _brains cause minds_ , and _syntax doesn't suffice_ _for semantics_ . Its target, Searle dubs "strong AI": "according to strong AI," according to Searle, "the computer is not merely a tool in the study of the mind, rather the appropriately programmed computer really _is_ a mind in the sense that computers given the right programs can be literally said to _understand_ and have other cognitive states" 1980a, p. 417). Searle contrasts "strong AI" to "weak AI". According to weak AI, according to Searle, computers just
• Larry Hauser (online). The chinese room argument.   (Abstract & more)
  Abstract: _The Chinese room argument_ - John Searle's (1980a) thought experiment and associated (1984) derivation - is one of the best known and widely credited counters to claims of artificial intelligence (AI), i.e., to claims that computers _do_ or at least _can_ (someday might) think. According to Searle's original presentation, the argument is based on two truths: _brains cause minds_ , and _syntax doesn't_ _suffice for semantics_ . Its target, Searle dubs "strong AI": "according to strong AI," according to Searle, "the computer is not merely a tool in the study of the mind, rather the appropriately programmed computer really _is_ a mind in the sense that computers given the right programs can be literally said to _understand_ and have other cognitive states" (1980a, p. 417). Searle contrasts "strong AI" to "weak AI". According to weak AI, according to Searle, computers just
• Patrick Hayes, Stevan Harnad, Donald R. Perlis & Ned Block (1992). Virtual symposium on virtual mind.   (Abstract & more)
  Abstract:   When certain formal symbol systems (e.g., computer programs) are implemented as dynamic physical symbol systems (e.g., when they are run on a computer) their activity can be interpreted at higher levels (e.g., binary code can be interpreted as LISP, LISP code can be interpreted as English, and English can be interpreted as a meaninguful conversation). These higher levels of interpretability are called ‘virtual’ systems. If such a virtual system is interpretable as if it had a mind, is such a ‘virtual mind’ real? This is the question addressed in this ‘virtual’ symposium, originally conducted electronically among four cognitive scientists. Donald Perlis, a computer scientist, argues that according to the computationalist thesis, virtual minds are real and hence Searle's Chinese Room Argument fails, because if Searle memorized and executed a program that could pass the Turing Test in Chinese he would have a second, virtual, Chinese-understanding mind of which he was unaware (as in multiple personality). Stevan Harnad, a psychologist, argues that Searle's Argument is valid, virtual minds are just hermeneutic overinterpretations, and symbols must be grounded in the real world of objects, not just the virtual world of interpretations. Computer scientist Patrick Hayes argues that Searle's Argument fails, but because Searle does not really implement the program: a real implementation must not be homuncular but mindless and mechanical, like a computer. Only then can it give rise to a mind at the virtual level. Philosopher Ned Block suggests that there is no reason a mindful implementation would not be a real one
  Additional links for this entry:
  http://eprints.resist.ecs.soton.ac.uk/3371/
  http://eprints.ecs.soton.ac.uk/archive/00003371/
  http://eprints.ecs.soton.ac.uk/archive/00003371/
  http://cogprints.org/1585/0/harnad92.virtualmind.html
  http://cogprints.org/1585/00/harnad92.virtualmind.html
  http://cogprints.org/1585/00/harnad92.virtualmind.html
  http://cogprints.soton.ac.uk/documents/disk0/00/00/15/85/
  http://cogprints.soton.ac.uk/documents/disk0/00/00/15/85/
  http://cogsci.soton.ac.uk/harnad/Papers/Harnad/harnad92.virtualmind.html
  http://cogsci.soton.ac.uk/harnad/Papers/Harnad/harnad92.virtualmind.html
  http://cogsci.soton.ac.uk/~harnad/Papers/Harnad/harnad92.virtualmind.html
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad92.virtualmind.html
  http://cogsci.soton.ac.uk/~harnad/Papers/Harnad/harnad92.virtualmind.html
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad92.virtualmind.html
  http://eprints.ecs.soton.ac.uk/archive/00003371/02/harnad92.virtualmind.html
  http://cogprints.ecs.soton.ac.uk/archive/00001585/00/harnad92.virtualmind.html
  http://cogprints.ecs.soton.ac.uk/archive/00001585/00/harnad92.virtualmind.html
  http://citebase.eprints.org/cgi-bin/citations?id=oai:eprints.ecs.soton.ac.uk:3371
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:1585
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:1585
  http://www.springerlink.com/content/g2063372459ww766/fulltext.pdf
  http://www.springerlink.com/index/G2063372459WW766.pdf
  
• C. Kaernbach (2005). No virtual mind in the chinese room.   (More)
  Additional links for this entry:
  http://www.psychologie.uni-kiel.de/emotion/team/kaernbach/publications/2005_kae_jcs.pdf
  http://www.ingentaconnect.com/content/imp/jcs/2005/00000012/00000011/art00002
  
• Robert W. Kentridge (2001). Computation, chaos and non-deterministic symbolic computation: The chinese room problem solved?   (More)
  Additional links for this entry:
  http://cogsci.soton.ac.uk/~harnad/Temp/Think/kentridg.htm
  http://www.cogsci.ecs.soton.ac.uk/cgi/psyc/newpsy?article=12.050
  http://www.cogsci.ecs.soton.ac.uk/cgi/psyc/newpsy?symbolism-connectionism.17
  http://cogsci.soton.ac.uk/~harnad/Papers/Harnad/harnad93.symb.anal.net.kentridge.html
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad93.symb.anal.net.kentridge.html
  http://psycprints.ecs.soton.ac.uk/archive/00000179/02/psyc.01.12.050.symbolism-connectionism.17.kentridge
  
• Kevin B. Korb (1991). Searle's AI program.   (More)
  Additional links for this entry:
  http://www.informaworld.com/index/776648442.pdf
  
• Diane Law (online). Searle, subsymbolic functionalism, and synthetic intelligence.   (More)
  Additional links for this entry:
  http://nn.cs.utexas.edu/downloads/papers/law.synthetic.pdf
  http://nn.cs.utexas.edu/downloads/papers/law.synthetic.ps.gz
  http://www.cs.utexas.edu/users/nn/downloads/papers/law.synthetic.pdf
  http://www.cs.utexas.edu/ftp/pub/neural-nets/papers/law.synthetic.pdf
  http://staticred.net/huco/617/searle-subsymbolic-functionalism-and.pdf
  http://www.let.rug.nl/~nerbonne/teach/neuro/kleiweg/law.synthetic.ps.gz
  http://odur.let.rug.nl/~nerbonne/teach/neuro/kleiweg/law.synthetic.ps.gz
  http://historical.ncstrl.org/litesite-data/utexas_cs/UT-AI-TR-94-222.ps.Z
  http://www.phil.canterbury.ac.nz/tom_bestor/e-texts/Law, Diane - Searle, subsymbolic functionalism and synthetic understanding law.synthetic.ps
  
• Alan M. Leslie & Brian J. Scholl (1999). Modularity, development and 'theory of mind'.   (Abstract & more)
  Abstract: Psychologists and philosophers have recently been exploring whether the mechanisms which underlie the acquisition of ‘theory of mind’ (ToM) are best charac- terized as cognitive modules or as developing theories. In this paper, we attempt to clarify what a modular account of ToM entails, and why it is an attractive type of explanation. Intuitions and arguments in this debate often turn on the role of develop- ment: traditional research on ToM focuses on various developmental sequences, whereas cognitive modules are thought to be static and ‘anti-developmental’. We suggest that this mistaken view relies on an overly limited notion of modularity, and we explore how ToM might be grounded in a cognitive module and yet still afford development. Modules must ‘come on-line’, and even fully developed modules may still develop internally, based on their constrained input. We make these points con- crete by focusing on a recent proposal to capture the development of ToM in a module via parameterization
  Additional links for this entry:
  http://l3d.cs.colorado.edu/~ctg/classes/lib/cogsci/scholl.pdf
  http://ruccs.rutgers.edu/~aleslie/99-Scholl-Leslie-MindLang.pdf
  http://ruccs.rutgers.edu/~aleslie/99-Scholl-Leslie-MindLang.pdf
  http://www.cs.colorado.edu/~duck/ctg/classes/lib/cogsci/scholl.pdf
  http://www.blackwell-synergy.com/doi/abs/10.1111/1468-0017.00106?favorite=add
  http://www.blackwell-synergy.com/links/doi/10.1111/1468-0017.00106
  http://www.ingentaconnect.com/content/bpl/mila/1999/00000014/00000001/art00106
  
• John McCarthy (online). John Searle's chinese room argument.   (Abstract & more)
  Abstract: John Searle begins his (1990) ``Consciousness, Explanatory Inversion and Cognitive Science'' with

  ``Ten years ago in this journal I published an article (Searle, 1980a and 1980b) criticising what I call Strong
  AI, the view that for a system to have mental states it is sufficient for the system to implement the right sort of
  program with right inputs and outputs. Strong AI is rather easy to refute and the basic argument can be
  summarized in one sentence: {it a system, me for example, could implement a program for understanding
  Chinese, for example, without understanding any Chinese at all.} This idea, when developed, became
  known as the Chinese Room Argument.''

  The Chinese Room Argument can be refuted in one sentence
• Ethan Mitchell (2008). The real Chinese Room.   (More)
• John R. Searle (1990). Is the brain's mind a computer program?   (More)
  Additional links for this entry:
  http://books.google.com/books?hl=en&lr=&id=hQCzOmaGeVYC&oi=fnd&pg=PA264&ots=j6aih-FnAo&sig=S9z08wWdwwt3psKgZPsRfS-1bXE
  
• John R. Searle (1980). Minds, brains and programs.   (Abstract & more)
  Abstract: What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI (artificial intelligence). According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to..
  Additional links for this entry:
  http://courses.washington.edu/info300/searle.pdf
  http://pami.uwaterloo.ca/tizhoosh/docs/Searle.pdf
  http://www.ifispan.waw.pl/~rpilat/john_searle.pdf
  http://members.aol.com/NeoNoetics/MindsBrainsPrograms.html
  http://www.bbsonline.org/Preprints/OldArchive/bbs.searle2.html
  http://staticred.net/huco/617/searle-minds, brains, and programs.pdf
  http://www.bbsonline.org/documents/a/00/00/04/84/bbs00000484-00/bbs.searle2.html
  http://amor.rz.hu-berlin.de/~h0998dgh/philom/computational_mind/searle_Minds, Brains, and Programs.htm
  http://books.google.com/books?hl=en&lr=&id=CEMYUU_HFMAC&oi=fnd&pg=PA201&ots=dMdcPQ709B&sig=IAV-tI3UMUrdII-jhXVCiE5EiNY
  http://books.google.com/books?hl=en&lr=&id=CEMYUU_HFMAC&oi=fnd&pg=PA201&ots=dLmgQW13bB&sig=e696dd_RJUp-z7nJq_VUVkJ6Vco
  http://books.google.com/books?hl=en&lr=&id=CEMYUU_HFMAC&oi=fnd&pg=PA201&ots=dMdgLT5-bF&sig=WhrAW9GsnXpijAGLjoTnMSl83U4
  http://books.google.com/books?hl=en&lr=&id=CEMYUU_HFMAC&oi=fnd&pg=PA201&ots=dMdeTS616J&sig=Gup1URzClmw94-tEdiKkRv8oo_E
  http://books.google.com/books?hl=en&lr=&id=CEMYUU_HFMAC&oi=fnd&pg=PA201&ots=dMdfPT1-fI&sig=NuhA3CnAPDnsWqo8Ta8-RX2cCEY
  http://books.google.com/books?hl=en&lr=&id=CEMYUU_HFMAC&oi=fnd&pg=PA201&ots=dLmgLS63cA&sig=lNvUnhfC6Xi8TMG19ynGzF7-UrE
  http://books.google.com/books?hl=en&lr=&id=CEMYUU_HFMAC&oi=fnd&pg=PA201&ots=dMdeNS1ZcF&sig=6EzNiu7H_1bXLA0zJ16b39NuIVQ
  http://books.google.com/books?hl=en&lr=&id=CEMYUU_HFMAC&oi=fnd&pg=PA201&ots=dMdiPV7_dJ&sig=xzN-ebbJvEML3FULifpKsvbJ4B0
  http://books.google.com/books?hl=en&lr=&id=CEMYUU_HFMAC&oi=fnd&pg=PA201&ots=dLmgOW03aF&sig=v25MYgLHP7PRb5D3u6V0j21p3Os
  http://books.google.com/books?hl=en&lr=&id=CEMYUU_HFMAC&oi=fnd&pg=PA201&ots=dMdhTV4ZdG&sig=_xvxtHTY2CziSv0BQSRuTeAcVyE
  http://books.google.com/books?hl=en&lr=&id=CEMYUU_HFMAC&oi=fnd&pg=PA201&ots=dMddRR63eF&sig=LYLLmE8CSwbq9blXRhOQWNiQKBo
  http://books.google.com/books?hl=en&lr=&id=CEMYUU_HFMAC&oi=fnd&pg=PA201&ots=dMddLR2XfE&sig=hPqWXhv4YdFnGCjtMhQpRctFDz8
  http://books.google.com/books?hl=en&lr=&id=CEMYUU_HFMAC&oi=fnd&pg=PA201&ots=dMdgRU01eJ&sig=PuxfSwx103nfQfLP8luU4Z-hgSc
  http://books.google.com/books?hl=en&lr=&id=CEMYUU_HFMAC&oi=fnd&pg=PA201&ots=dMdhNV0_7I&sig=JxSMo440evbsIv2dv4QpEJVAC4A
  
• Aaron Sloman (1986). Did Searle attack strong strong AI or weak strong AI?   (More)
  Additional links for this entry:
  http://www.cs.bham.ac.uk/research/cogaff/sloman.searle.85.text
  
• Mark D. Sprevak (online). Algorithms and the chinese room.   (More)
• Jerome C. Wakefield (2003). The chinese room argument reconsidered: Essentialism, indeterminacy, and strong AI.   (Abstract & more)
  Abstract:   I argue that John Searle's (1980) influential Chinese room argument (CRA) against computationalism and strong AI survives existing objections, including Block's (1998) internalized systems reply, Fodor's (1991b) deviant causal chain reply, and Hauser's (1997) unconscious content reply. However, a new ``essentialist'' reply I construct shows that the CRA as presented by Searle is an unsound argument that relies on a question-begging appeal to intuition. My diagnosis of the CRA relies on an interpretation of computationalism as a scientific theory about the essential nature of intentional content; such theories often yield non-intuitive results in non-standard cases, and so cannot be judged by such intuitions. However, I further argue that the CRA can be transformed into a potentially valid argument against computationalism simply by reinterpreting it as an indeterminacy argument that shows that computationalism cannot explain the ordinary distinction between semantic content and sheer syntactic manipulation, and thus cannot be an adequate account of content. This conclusion admittedly rests on the arguable but plausible assumption that thought content is interestingly determinate. I conclude that the viability of computationalism and strong AI depends on their addressing the indeterminacy objection, but that it is currently unclear how this objection can be successfully addressed
  Additional links for this entry:
  http://www.springerlink.com/content/q76u712262711110/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=5115346&PDF=1
  http://www.springerlink.com/index/Q76U712262711110.pdf
  http://www.ingentaconnect.com/content/klu/mind/2003/00000013/00000002/05115346
  

Machine Consciousness

• William Y. Adams (online). Intersubjective transparency and artificial consciousness.   (More)
• Igor L. Aleksander (2007). Machine consciousness.   (More)
  Additional links for this entry:
  http://books.google.com/books?hl=en&lr=&id=YHGacGKyVbYC&oi=fnd&pg=PA99&ots=SSSQPkbxBS&sig=LmbDUzP5IccBZCh8TG02TqZZL28
  http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=16186018&dopt=Citation
  http://www.ncbi.nlm.nih.gov/sites/entrez?db=pubmed&uid=16186018&cmd=showdetailview&indexed=google
  
• Igor L. Aleksander (2006). Machine consciousness.   (More)
  Additional links for this entry:
  http://books.google.com/books?hl=en&lr=&id=YHGacGKyVbYC&oi=fnd&pg=PA99&ots=SSSQPkbzBY&sig=dSV8_pheTWTgsxz7NiRaIDipYNs
  http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=16186018&dopt=Citation
  http://www.ncbi.nlm.nih.gov/sites/entrez?db=pubmed&uid=16186018&cmd=showdetailview&indexed=google
  
• Richard L. Amoroso (1997). The theoretical foundations for engineering a conscious quantum computer.   (More)
  Additional links for this entry:
  http://www.mindspring.com/~noetic.advanced.studies/Amoroso19.pdf
  
• R. Arrabales & A. Sanchis (forthcoming). Applying machine consciousness models in autonomous situated agents.   (More)
• John L. Bell (online). Algorithmicity and consciousness.   (Abstract & more)
  Abstract: Why should one believe that conscious awareness is solely the result of organizational complexity? What is the connection between consciousness and combinatorics: transformation of quantity into quality? The claim that the former is reducible to the other seems unconvincing—as unlike as chalk and cheese! In his book1 Penrose is at least attempting to compare like with like: the enigma of consciousness with the progress of physics
• Selmer Bringsjord (1994). Could, how could we tell if, and should - androids have inner lives?   (More)
• Selmer Bringsjord (2004). On building robot persons: Response to Zlatev.   (Abstract & more)
  Abstract:   Zlatev offers surprisingly weak reasoning in support of his view that robots with the right kind of developmental histories can have meaning. We ought nonetheless to praise Zlatev for an impressionistic account of how attending to the psychology of human development can help us build robots that appear to have intentionality
  Additional links for this entry:
  http://portal.acm.org/citation.cfm?id=1011949.1011965
  http://www.cogs.indiana.edu/cogx/robotperson_Zlatev_response.pdf
  http://www.springerlink.com/content/w83402573w376q55/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=5274048&PDF=1
  http://www.springerlink.com/index/W83402573W376Q55.pdf
  http://www.ingentaconnect.com/content/klu/mind/2004/00000014/00000003/05274048
  
• Scott Brockmeier (1997). Computational architecture and the creation of consciousness.   (More)
• G. Buttazzo (2001). Artificial consciousness: Utopia or real possibility?   (More)
  Additional links for this entry:
  http://feanor.sssup.it/~giorgio/paps/2001/ieeecm01.pdf
  http://csdl.computer.org/comp/mags/co/2001/07/r7024abs.htm
  http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=933500
  http://www.das.ufsc.br/~rabelo/Ensino/DAS6607/Artigos-Gerais/ArtificialConsciousness.pdf
  http://www.csa.com/partners/viewrecord.php?requester=gs&collection=TRD&recid=20061053096677MT&recid=20061090133720CI&recid=20061023229829EA
  
• G. Caplain (1995). Is consciousness a computational property?   (More)
  Additional links for this entry:
  http://books.google.com/books?hl=en&lr=&id=VHZy4j_Qa-cC&oi=fnd&pg=PA190&ots=RjBGledukl&sig=Oa-FArSWce_2jXSLqmlPHTdqlZc
  
• Rodney M. J. Cotterill (2003). Cyberchild: A simulation test-bed for consciousness studies.   (More)
• Daniel C. Dennett (1997). Consciousness in Human and Robot Minds.   (Abstract & more)
  Abstract: The best reason for believing that robots might some day become conscious is that we human beings are conscious, and we are a sort of robot ourselves. That is, we are extraordinarily complex self-controlling, self-sustaining physical mechanisms, designed over the eons by natural selection, and operating according to the same well-understood principles that govern all the other physical processes in living things: digestive and metabolic processes, self-repair and reproductive processes, for instance. It may be wildly over-ambitious to suppose that human artificers can repeat Nature's triumph, with variations in material, form, and design process, but this is not a deep objection. It is not as if a conscious machine contradicted any fundamental laws of nature, the way a perpetual motion machine does. Still, many skeptics believe--or in any event want to believe--that it will never be done. I wouldn't wager against them, but my reasons for skepticism are mundane, economic reasons, not theoretical reasons
  Additional links for this entry:
  http://cogprints.org/429/00/concrobt.htm
  http://ase.tufts.edu/cogstud/papers/concrobt.htm
  http://cogprints.ecs.soton.ac.uk/archive/00000429/
  http://cogprints.ecs.soton.ac.uk/archive/00000429/00/concrobt.htm
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:429
  
• Daniel C. Dennett (1994). The practical requirements for making a conscious robot.   (Abstract & more)
  Abstract: Arguments about whether a robot could ever be conscious have been conducted up to now in the factually impoverished arena of what is possible "in principle." A team at MIT of which I am a part is now embarking on a longterm project to design and build a humanoid robot, Cog, whose cognitive talents will include speech, eye-coordinated manipulation of objects, and a host of self-protective, self-regulatory and self-exploring activities. The aim of the project is not to make a conscious robot, but to make a robot that can interact with human beings in a robust and versatile manner in real time, take care of itself, and tell its designers things about itself that would otherwise be extremely difficult if not impossible to determine by examination. Many of the details of Cog's "neural" organization will parallel what is known (or presumed known) about their counterparts in the human brain, but the intended realism of Cog as a model is relatively coarse-grained, varying opportunistically as a function of what we think we know, what we think we can build, and what we think doesn't matter. Much of what we think will of course prove to be mistaken; that is one advantage of real experiments over thought experiments
  Additional links for this entry:
  http://adsabs.harvard.edu/abs/1994RSPTA.349..133D
  http://www.journals.royalsoc.ac.uk/index/L62130158Q786731.pdf
  http://cogsci.soton.ac.uk/~harnad/Papers/Py104/dennett.rob.html
  http://links.jstor.org/sici?sici=0962-8428(19941015)349:1689<133:TPRFMA>2.0.CO;2-1
  
• Wlodizislaw Duch (2005). Brain-inspired conscious computing architecture.   (More)
  Additional links for this entry:
  http://citeseer.ist.psu.edu/duch05braininspired.html
  http://www.phys.uni.torun.pl/publications/kmk/03-Brainins.pdf
  http://www.phys.uni.torun.pl/publications/kmk/03-Brainins.html
  http://cogprints.ecs.soton.ac.uk/archive/00003319/01/03-Brainins.pdf
  
• Stan Franklin (2003). Ida: A conscious artifact?   (More)
  Additional links for this entry:
  http://csrg.cs.memphis.edu/csrg/assets/papers/IDA-ConsciousArtifact.doc
  
• Stevan Harnad (2003). Can a machine be conscious? How?   (Abstract & more)
  Abstract: A "machine" is any causal physical system, hence we are machines, hence machines can be conscious. The question is: which kinds of machines can be conscious? Chances are that robots that can pass the Turing Test -- completely indistinguishable from us in their behavioral capacities -- can be conscious (i.e. feel), but we can never be sure (because of the "other-minds" problem). And we can never know HOW they have minds, because of the "mind/body" problem. We can only know how they pass the Turing Test, but not how, why or whether that makes them feel
  Additional links for this entry:
  http://cogprints.org/2460/
  http://eprints.ecs.soton.ac.uk/7718
  http://cogprints.org/5330/1/machine.htm
  http://cogprints.org/2460/1/machine.htm
  http://eprints.resist.ecs.soton.ac.uk/7718/
  http://eprints.ecs.soton.ac.uk/archive/00007718/
  http://cogsci.soton.ac.uk/~harnad/Temp/machine.htm
  http://cogprints.ecs.soton.ac.uk/archive/00002460/
  http://www.ecs.soton.ac.uk/~harnad/Temp/machine.htm
  http://cogprints.ecs.soton.ac.uk/archive/00002460/01/machine.htm
  http://citebase.eprints.org/cgi-bin/citations?id=oai:cogprints.soton.ac.uk:2460
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:2460
  http://www.ingentaconnect.com/content/imp/jcs/2003/00000010/F0020004/1347
  http://users.ecs.soton.ac.uk/~harnad/Temp/machine.htm
  
• Owen Holland & Russell B. Goodman (2003). Robots with internal models: A route to machine consciousness?   (More)
  Additional links for this entry:
  http://www.ingentaconnect.com/content/imp/jcs/2003/00000010/F0020004/1348
  http://www.ingentaconnect.com/content/imp/jcs/2003/00000010/F0020004/1342
  
• William G. Lycan (1998). Qualitative experience in machines.   (More)
• Hugh J. McCann (2005). Intentional action and intending: Recent empirical studies.   (Abstract & more)
  Abstract: Recent empirical work calls into question the so-called Simple View that an agent who A’s intentionally intends to A. In experimental studies, ordinary speakers frequently assent to claims that, in certain cases, agents who knowingly behave wrongly intentionally bring about the harm they do; yet the speakers tend to deny that it was the intention of those agents to cause the harm. This paper reports two additional studies that at first appear to support the original ones, but argues that in fact, the evidence of all the studies considered is best understood in terms of the Simple View.
  Additional links for this entry:
  http://instruct1.cit.cornell.edu/courses/phi663/knobe McCann.pdf
  http://www.informaworld.com/index/727334015.pdf
  http://taylorandfrancis.metapress.com/index/RP912503N228W554.pdf
  http://www.unc.edu/~knobe/McCann.pdf
  http://www.ingentaconnect.com/content/routledg/cphp/2005/00000018/00000006/art00005
  
• John McCarthy (1996). Making robots conscious of their mental states.   (Abstract & more)
  Abstract: In AI, consciousness of self consists in a program having certain kinds of facts about its own mental processes and state of mind. We discuss what consciousness of its own mental structures a robot will need in order to operate in the common sense world and accomplish the tasks humans will give it. It's quite a lot. Many features of human consciousness will be wanted, some will not, and some abilities not possessed by humans have already been found feasible and useful in limited contexts. We give preliminary fragments of a logical language a robot can use to represent information about its own state of mind. A robot will often have to conclude that it cannot decide a question on the basis of the information in memory and therefore must seek information externally. Gödel's idea of relative consistency is used to formalize non-knowledge. Programs with the kind of consciousness discussed in this article do not yet exist, although programs with some components of it exist. Thinking about consciousness with a view to designing it provides a new approach to some of the problems of consciousness studied by philosophers. One advantage is that it focusses on the aspects of consciousness important for intelligent behavior
  Additional links for this entry:
  http://citeseer.ist.psu.edu/81449.html
  http://cogprints.org/422/00/consciousness.ps
  http://citeseer.ist.psu.edu/mccarthy95making.html
  http://cogprints.ecs.soton.ac.uk/archive/00000422/
  http://www-formal.stanford.edu/jmc/consciousness.ps
  http://portal.acm.org/citation.cfm?id=647636.733058
  http://www-formal.stanford.edu/jmc/consciousness/consciousness.html
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:422
  
• Drew McDermott (2007). Artificial intelligence and consciousness.   (More)
• Alfred R. Mele (2006). The folk concept of intentional action: A commentary.   (Abstract & more)
  Abstract: In this commentary, I discuss the three main articles in this volume that present survey data relevant to a search for something that might merit the label “the folk concept of intentional action” – the articles by Joshua Knobe and Arudra Burra, Bertram Malle, and Thomas Nadelhoffer. My guiding question is this: What shape might we find in an analysis of intentional action that takes at face value the results of all of the relevant surveys about vignettes discussed in these three articles?1 To simplify exposition, I assume that there is something that merits the label I mentioned
  Additional links for this entry:
  http://www.unc.edu/~knobe/MeleJCC.pdf
  http://www.springerlink.com/index/0P30736376436T04.pdf
  http://www.ingentaconnect.com/content/brill/jocc/2006/00000006/F0020001/art00016
  
• Marvin L. Minsky (1991). Conscious machines.   (More)
• Marc A. Moffett & Jennifer Cole Wright (online). The folk on know-how: Why radical intellectualism does not over-intellectualize.   (Abstract & more)
  Abstract: Philosophical discussion of the nature of know-how has focused on the relation between know-how and ability. Broadly speaking, neo-Ryleans attempt to identify know-how with a certain type of ability,1 while, traditionally, intellectualists attempt to reduce it to some form of propositional knowledge. For our purposes, however, this characterization of the debate is too crude. Instead, we prefer the following more explicit taxonomy. Anti-intellectualists, as we will use the term, maintain that knowing how to ? entails the ability to ?. Dispositionalists maintain that the ability to ? is sufficient (modulo some fairly innocuous constraints) for knowing how to ?. Intellectualists, as we will use the term, deny the anti-intellectualist claim. Finally, radical intellectualists deny both the anti-intellectualist and dispositionalist claims. Pace neo-Ryleans (who in our taxonomy are those who accept both dispositionalism and anti-intellectualism), radical intellectualists maintain that the ability to ? is neither necessary nor sufficient for knowing how to ?
• Shaun Nichols (2004). Folk concepts and intuitions: From philosophy to cognitive science.   (Abstract & more)
  Abstract: Analytic philosophers have long used a priori methods to characterize folk concepts like knowledge, belief, and wrongness. Recently, researchers have begun to exploit social scientific methodologies to characterize such folk concepts. One line of work has explored folk intuitions on cases that are disputed within philosophy. A second approach, with potentially more radical implications, applies the methods of cross-cultural psychology to philosophical intuitions. Recent work suggests that people in different cultures have systematically different intuitions surrounding folk concepts like wrong, knows, and refers. A third strand of research explores the emergence and character of folk concepts in children. These approaches to characterizing folk concepts provide important resources that will supplement, and perhaps sometimes displace, a priori approaches
  Additional links for this entry:
  http://dingo.sbs.arizona.edu/~snichols/Papers/FolkConcepts.pdf
  http://matrix.aklab.psych.ubc.ca/uploads/Christine_FolkPhilosophy_TICS.pdf
  http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=15491906&dopt=Citation
  http://www.ncbi.nlm.nih.gov/sites/entrez?db=pubmed&uid=15491906&cmd=showdetailview&indexed=google
  http://linkinghub.elsevier.com/retrieve/pii/S1364661304002360
  
• Steven Pinker (online). Could a computer ever be conscious?   (More)
• Richard H. Schlagel (1999). Why not artificial consciousness or thought?   (Abstract & more)
  Abstract:   The purpose of this article is to show why consciousness and thought are not manifested in digital computers. Analyzing the rationale for claiming that the formal manipulation of physical symbols in Turing machines would emulate human thought, the article attempts to show why this proved false. This is because the reinterpretation of designation and meaning to accommodate physical symbol manipulation eliminated their crucial functions in human discourse. Words have denotations and intensional meanings because the brain transforms the physical stimuli received from the microworld into a qualitative, macroscopic representation for consciousness. Lacking this capacity as programmed machines, computers have no representations for their symbols to designate and mean. Unlike human beings in which consciousness and thought, with their inherent content, have emerged because of their organic natures, serial processing computers or parallel distributed processing systems, as programmed electrical machines, lack these causal capacities
  Additional links for this entry:
  http://www.csa.com/partners/viewrecord.php?requester=gs&collection=TRD&recid=467237CI
  http://www.springerlink.com/content/k248165u513p4746/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=187743&PDF=1
  http://www.springerlink.com/index/K248165U513P4746.pdf
  http://www.ingentaconnect.com/content/klu/mind/1998/00000009/00000001/00187743
  
• Mark F. Sharlow (ms). Can machines have first-person properties?   (Abstract & more)
  Abstract: One of the most important ongoing debates in the philosophy of mind is the debate over the reality of the first-person character of consciousness.[1] Philosophers on one side of this debate hold that some features of experience are accessible only from a first-person standpoint. Some members of this camp, notably Frank Jackson, have maintained that epiphenomenal properties play roles in consciousness [2]; others, notably John R. Searle, have rejected dualism and regarded mental phenomena as entirely biological.[3] In the opposite camp are philosophers who hold that all mental capacities are in some sense computational - or, more broadly, explainable in terms of features of information processing systems.[4] Consistent with this explanatory agenda, members of this camp normally deny that any aspect of mind is accessible solely from a first-person standpoint. This denial sometimes goes very far - even as far as Dennett's claim that the phenomenology of conscious experience does not really exist
• Aaron Sloman & Ronald L. Chrisley (2003). Virtual machines and consciousness.   (More)
  Additional links for this entry:
  http://citeseer.ist.psu.edu/sloman02virtual.html
  http://www.cs.bham.ac.uk/research/cogaff/sloman-chrisley-jcs.pdf
  http://www.cs.bham.ac.uk/research/cogaff/sloman-chrisley-jcs03.pdf
  http://www.cs.memphis.edu/~franklin/documents/sloman-chrisley-jcs.pdf
  http://www.msci.memphis.edu/~franklin/documents/sloman-chrisley-jcs.pdf
  http://www.ingentaconnect.com/content/imp/jcs/2003/00000010/F0020004/1350
  
• Vincenzo Tagliasco (2007). Artificial consciousness: A technological discipline.   (More)
• William I. Thompson (2003). The Borg or Borges?   (More)
  Additional links for this entry:
  http://www.ingentaconnect.com/content/imp/jcs/2003/00000010/F0020004/1352
  

Machine Mentality, Misc

• John Beloff (2002). Minds or machines.   (More)
• Margaret A. Boden (1995). Could a robot be creative--and would we know?   (More)
  Additional links for this entry:
  http://kogs-www.informatik.uni-hamburg.de/~neumann/Denkmaschinen-SS-2005/Vortrag-14.6.05.pdf
  
• Nick Bostrom (2003). Taking intelligent machines seriously: Reply to critics.   (Abstract & more)
  Abstract: In an earlier paper in this journal[1], I sought to defend the claims that (1) substantial probability should be assigned to the hypothesis that machines will outsmart humans within 50 years, (2) such an event would have immense ramifications for many important areas of human concern, and that consequently (3) serious attention should be given to this scenario. Here, I will address a number of points made by several commentators
  Additional links for this entry:
  http://www.questia.com/PM.qst?a=o&se=gglsc&d=5002030442
  http://linkinghub.elsevier.com/retrieve/pii/S0016328703000466
  http://www.ingentaconnect.com/content/els/00163287/2003/00000035/00000008/art00046
  
• Selmer Bringsjord (1998). Cognition is not computation: The argument from irreversibility.   (Abstract & more)
  Abstract:   The dominant scientific and philosophical view of the mind – according to which, put starkly, cognition is computation – is refuted herein, via specification and defense of the following new argument: Computation is reversible; cognition isn't; ergo, cognition isn't computation. After presenting a sustained dialectic arising from this defense, we conclude with a brief preview of the view we would put in place of the cognition-is-computation doctrine
  Additional links for this entry:
  http://www.rpi.edu/~brings/SELPAP/irr.ps
  http://www.rpi.edu/~brings/SELPAP/irr.pdf
  http://citeseer.ist.psu.edu/bringsjord96cognition.html
  http://www.phil.canterbury.ac.nz/tom_bestor/e-texts/Bringsjord, selmer - cognition is not computation.pdf
  http://www.kluweronline.com/article.asp?PIPS=152330&PDF=1
  http://www.springerlink.com/index/N887505850J434UR.pdf
  http://www.ingentaconnect.com/content/klu/synt/1997/00000113/00000002/00152330
  http://www.springerlink.com/content/n887505850j434ur/fulltext.pdf
  
• Selmer Bringsjord (1994). Precis of What Robots Can and Can't Be.   (More)
• Gerard Casey (1992). Minds and machines.   (Abstract & more)
  Abstract: The emergence of electronic computers in the last thirty years has given rise to many interesting questions. Many of these questions are technical, relating to a machine’s ability to perform complex operations in a variety of circumstances. While some of these questions are not without philosophical interest, the one question which above all others has stimulated philosophical interest is explicitly non-technical and it can be expressed crudely as follows: Can a machine be said to think and, if so, in what sense? The issue has received much attention in the scholarly journals with articles and arguments appearing in great profusion, some resolutely answering this question in the affirmative, some, equally resolutely, answering this question in the negative, and others manifesting modified rapture. While the ramifications of the question are enormous I believe that the issue at the heart of the matter has gradually emerged from the forest of complications
• William A. Dembski (1999). Are we spiritual machines?   (Abstract & more)
  Abstract: For two hundred years materialist philosophers have argued that man is some sort of machine. The claim began with French materialists of the Enlightenment such as Pierre Cabanis, Julien La Mettrie, and Baron d’Holbach (La Mettrie even wrote a book titled Man the Machine). Likewise contemporary materialists like Marvin Minsky, Daniel Dennett, and Patricia Churchland claim that the motions and modifications of matter are sufficient to account for all human experiences, even our interior and cognitive ones. Whereas the Enlightenment philosophes might have thought of humans in terms of gear mechanisms and fluid flows, contemporary materialists think of humans in terms of neurological systems and computational devices. The idiom has been updated, but the underlying impulse to reduce mind to matter remains unchanged
• Daniel C. Dennett (1997). Did Hal committ murder?   (Abstract & more)
  Abstract: The first robot homicide was committed in 1981, according to my files. I have a yellowed clipping dated 12/9/81 from the Philadelphia Inquirer--not the National Enquirer--with the headline: Robot killed repairman, Japan reports The story was an anti-climax: at the Kawasaki Heavy Industries plant in Akashi, a malfunctioning robotic arm pushed a repairman against a gearwheel-milling machine, crushing him to death. The repairman had failed to follow proper instructions for shutting down the arm before entering the workspace. Why, indeed, had this industrial accident in Japan been reported in a Philadelphia newspaper? Every day somewhere in the world a human worker is killed by one machine or another. The difference, of course, was that in the public imagination at least, this was no ordinary machine; this was a robot, a machine that might have a mind, might have evil intentions, might be capable not just of homicide but of murder
  Additional links for this entry:
  http://ase.tufts.edu/cogstud/papers/didhal.htm
  
• Eric Drexler (1986). Thinking machines.   (More)
• Sanford C. Goldberg (1997). The very idea of computer self-knowledge and self-deception.   (Abstract & more)
  Abstract:   Do computers have beliefs? I argue that anyone who answers in the affirmative holds a view that is incompatible with what I shall call the commonsense approach to the propositional attitudes. My claims shall be two. First,the commonsense view places important constraints on what can be acknowledged as a case of having a belief. Second, computers – at least those for which having a belief would be conceived as having a sentence in a belief box – fail to satisfy some of these constraints. This second claim can best be brought out in the context of an examination of the idea of computer self-knowledge and self-deception, but the conclusion is perfectly general: the idea that computers are believers, like the idea that computers could have self-knowledge or be self-deceived, is incompatible with the commonsense view. The significance of the argument lies in the choice it forces on us: whether to revise our notion of belief so as to accommodate the claim that computers are believers, or to give up on that claim so as to preserve our pretheoretic notion of the attitudes. We cannot have it both ways
  Additional links for this entry:
  http://www.csa.com/partners/viewrecord.php?requester=gs&collection=TRD&recid=316238CI
  http://www.springerlink.com/content/x67006n334r1n383/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=136245&PDF=1
  http://www.springerlink.com/index/X67006N334R1N383.pdf
  http://www.ingentaconnect.com/content/klu/mind/1997/00000007/00000004/00136245
  
• Antoni Gomila (1995). From cognitive systems to persons.   (More)
• Larry Hauser (1993). Why isn't my pocket calculator a thinking thing?   (Abstract & more)
  Abstract: My pocket calculator (Cal) has certain arithmetical abilities: it seems Cal calculates. That calculating is thinking seems equally untendentious. Yet these two claims together provide premises for a seemingly valid syllogism whose conclusion -- Cal thinks -- most would deny. I consider several ways to avoid this conclusion, and find them mostly wanting. Either we ourselves can't be said to think or calculate if our calculation-like performances are judged by the standards proposed to rule out Cal; or the standards -- e.g., autonomy and self-consciousness -- make it impossible to verify whether anything or anyone (save myself) meets them. While appeals to the intentionality of thought or the unity of minds provide more credible lines of resistance, available accounts of intentionality and mental unity are insufficiently clear and warranted to provide very substantial arguments against Cal's title to be called a thinking thing. Indeed, considerations favoring granting that title are more formidable than generally appreciated
  Additional links for this entry:
  http://cogprints.org/242/0/wimpcatt.html
  http://cogprints.org/242/00/wimpcatt.html
  http://members.aol.com/lshauser/wimpcatt.html
  http://cogprints.ecs.soton.ac.uk/archive/00000242/
  http://cogprints.ecs.soton.ac.uk/archive/00000242/00/wimpcatt.html
  http://citebase.eprints.org/cgi-bin/citations?id=oai:cogprints.soton.ac.uk:242
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:242
  http://www.springerlink.com/content/t46235328605618l/fulltext.pdf
  http://www.springerlink.com/content/k5383t2m586208l4/fulltext.pdf
  http://www.springerlink.com/index/T46235328605618L.pdf
  http://www.springerlink.com/index/K5383T2M586208L4.pdf
  
• Michael Kary & Martin Mahner (2002). How would you know if you synthesized a thinking thing?   (Abstract & more)
  Abstract:   We confront the following popular views: that mind or life are algorithms; that thinking, or more generally any process other than computation, is computation; that anything other than a working brain can have thoughts; that anything other than a biological organism can be alive; that form and function are independent of matter; that sufficiently accurate simulations are just as genuine as the real things they imitate; and that the Turing test is either a necessary or sufficient or scientific procedure for evaluating whether or not an entity is intelligent. Drawing on the distinction between activities and tasks, and the fundamental scientific principles of ontological lawfulness, epistemological realism, and methodological skepticism, we argue for traditional scientific materialism of the emergentist kind in opposition to the functionalism, behaviourism, tacit idealism, and merely decorative materialism of the artificial intelligence and artificial life communities
  Additional links for this entry:
  http://www.springerlink.com/content/h8731k7036822314/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=390424&PDF=1
  http://www.springerlink.com/index/H8731K7036822314.pdf
  http://www.ingentaconnect.com/content/klu/mind/2002/00000012/00000001/00390424
  
• John T. Kearns (1997). Thinking machines: Some fundamental confusions.   (Abstract & more)
  Abstract:   This paper explores Church's Thesis and related claims madeby Turing. Church's Thesis concerns computable numerical functions, whileTuring's claims concern both procedures for manipulating uninterpreted marksand machines that generate the results that these procedures would yield. Itis argued that Turing's claims are true, and that they support (the truth of)Church's Thesis. It is further argued that the truth of Turing's and Church'sTheses has no interesting consequences for human cognition or cognitiveabilities. The Theses don't even mean that computers can do as much as peoplecan when it comes to carrying out effective procedures. For carrying out aprocedure is a purposive, intentional activity. No actual machine does, orcan do, as much
  Additional links for this entry:
  http://www.csa.com/partners/viewrecord.php?requester=gs&collection=TRD&recid=322375CI
  http://www.springerlink.com/content/p457647356006413/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=116417&PDF=1
  http://www.springerlink.com/index/P457647356006413.pdf
  http://www.ingentaconnect.com/content/klu/mind/1997/00000007/00000002/00116417
  
• Peter Kugel (2002). Computing machines can't be intelligent (...And Turing said so).   (Abstract & more)
  Abstract:   According to the conventional wisdom, Turing (1950) said that computing machines can be intelligent. I don''t believe it. I think that what Turing really said was that computing machines –- computers limited to computing –- can only fake intelligence. If we want computers to become genuinelyintelligent, we will have to give them enough initiative (Turing, 1948, p. 21) to do more than compute. In this paper, I want to try to develop this idea. I want to explain how giving computers more ``initiative'''' can allow them to do more than compute. And I want to say why I believe (and believe that Turing believed) that they will have to go beyond computation before they can become genuinely intelligent
  Additional links for this entry:
  http://www.cs.bc.edu/~kugel/Publications/Hyper.pdf
  http://www.cs.queensu.ca/home/akl/cisc879/papers/PAPERS_FROM_MINDS_AND_MACHINES/VOLUME_12_NO_4/P8T30NK152182338.pdf
  http://www.springerlink.com/content/p8t30nk152182338/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=5098145&PDF=1
  http://www.springerlink.com/index/P8T30NK152182338.pdf
  http://www.ingentaconnect.com/content/klu/mind/2002/00000012/00000004/05098145
  
• Jaron Lanier (ms). Mindless thought experiments (a critique of machine intelligence).   (Abstract & more)
  Abstract: Since there isn't a computer that seems conscious at this time, the idea of machine consciousness is supported by thought experiments. Here's one old chestnut: "What if you replaced your neurons one by one with neuron sized and shaped substitutes made of silicon chips that perfectly mimicked the chemical and electric functions of the originals? If you just replaced one single neuron, surely you'd feel the same. As you proceed, as more and more neurons are replaced, you'd stay conscious. Why wouldn't you still be conscious at the end of the process, when you'd reside in a brain shaped glob of silicon? And why couldn't the resulting replacement brain have been manufactured by some other means?"
• Douglas C. Long (1994). Why Machines Can Neither Think nor Feel.   (Abstract & more)
  Abstract: Over three decades ago, in a brief but provocative essay, Paul Ziff argued for the thesis that robots cannot have feelings because they are "mechanisms, not organisms, not living creatures. There could be a broken-down robot but not a dead one. Only living creatures can literally have feelings."[i] Since machines are not living things they cannot have feelings
• John McCarthy (1979). Ascribing mental qualities to machines.   (Abstract & more)
  Abstract: Ascribing mental qualities like beliefs, intentions and wants to a machine is sometimes correct if done conservatively and is sometimes necessary to express what is known about its state. We propose some new definitional tools for this: definitions relative to an approximate theory and second order structural definitions
  Additional links for this entry:
  http://cogprints.org/416/00/ascribing.ps
  http://www-formal.stanford.edu/jmc/ascribing.ps
  http://www-formal.stanford.edu/jmc/ascribing.pdf
  http://cogprints.ecs.soton.ac.uk/archive/00000416/00/ascribing.ps
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:416
  http://stinet.dtic.mil/oai/oai?verb=getRecord&metadataPrefix=html&identifier=ADA071423
  
• Marvin L. Minsky (1968). Matter, minds, models.   (More)
• Marvin L. Minsky (1982). Why people think computers can't.   (Abstract & more)
  Abstract: Most people think computers will never be able to think. That is, really think. Not now or ever. To be sure, most people also agree that computers can do many things that a person would have to be thinking to do. Then how could a machine seem to think but not actually think? Well, setting aside the question of what thinking actually is, I think that most of us would answer that by saying that in these cases, what the computer is doing is merely a superficial imitation of human intelligence. It has been designed to obey certain simple commands, and then it has been provided with programs composed of those commands. Because of this, the computer has to obey those commands, but without any idea of what's happening
  Additional links for this entry:
  http://web.media.mit.edu/~minsky/papers/ComputersCantThink.txt
  http://www.cogsci.northwestern.edu/courses/cg207/readings/AIMag03-04-001.pdf
  http://cs.clarku.edu/~jbreecher/public/2005_Can_Computers_Think/Minsky-WhyPeopleThinkComputersCant.pdf
  http://aleph0.clarku.edu/~jbreecher/public/2005_Can_Computers_Think/Minsky-WhyPeopleThinkComputersCant.pdf
  http://act-r.psy.cmu.edu/~douglass/Douglass/Agents/TopicPapers/~TopCandidates~/State-of-AI/AIMag03-04-001.pdf
  
• Bence Nanay (2006). Symmetry between the intentionality of minds and machines? The biological plausibility of Dennett's position.   (Abstract & more)
  Abstract: One of the most influential arguments against the claim that computers can think is that while our intentionality is intrinsic, that of computers is derived: it is parasitic on the intentionality of the programmer who designed the computer-program. Daniel Dennett chose a surprising strategy for arguing against this asymmetry: instead of denying that the intentionality of computers is derived, he endeavours to argue that human intentionality is derived too. I intend to examine that biological plausibility of Dennett’s suggestion and show that Dennett’s argument for the claim that human intentionality is derived because it was designed by natural selection is based on the misunderstanding of how natural selection works
  Additional links for this entry:
  http://www.springerlink.com/content/a44653240255k3g2/fulltext.pdf
  http://www.springerlink.com/index/A44653240255K3G2.pdf
  
• Diane Proudfoot (2004). The implications of an externalist theory of rule-following behavior for robot cognition.   (Abstract & more)
  Abstract:   Given (1) Wittgensteins externalist analysis of the distinction between following a rule and behaving in accordance with a rule, (2) prima facie connections between rule-following and psychological capacities, and (3) pragmatic issues about training, it follows that most, even all, future artificially intelligent computers and robots will not use language, possess concepts, or reason. This argument suggests that AIs traditional aim of building machines with minds, exemplified in current work on cognitive robotics, is in need of substantial revision
  Additional links for this entry:
  http://www.springerlink.com/content/v3gpx4k76m46705k/fulltext.pdf
  http://www.springerlink.com/index/V3GPX4K76M46705K.pdf
  http://www.ingentaconnect.com/content/klu/mind/2004/00000014/00000003/05268464
  
• Zenon W. Pylyshyn (1975). Minds, machines and phenomenology: Some reflections on Dreyfus' What Computers Can't Do.   (More)
• William J. Rapaport (online). Computer processes and virtual persons: Comments on Cole's "artificial intelligence and personal identity".   (Abstract & more)
  Abstract: This is a draft of the written version of comments on a paper by David Cole, presented orally at the American Philosophical Association Central Division meeting in New Orleans, 27 April 1990. Following the written comments are 2 appendices: One contains a letter to Cole updating these comments. The other is the handout from the oral presentation
  Additional links for this entry:
  http://www.cse.buffalo.edu/tech-reports/90-13.ps
  http://www.cse.buffalo.edu/tech-reports/90-13.ps.Z
  http://www.cse.buffalo.edu/~rapaport/Papers/cole.tr.17my90.pdf
  http://www.cse.buffalo.edu/~rapaport/Papers/cole.tr.17my90.pdf
  http://historical.ncstrl.org/litesite-data/suny_buffalo_cs/90-13.ps.Z
  
• Graeme Ritchie (2007). Some empirical criteria for attributing creativity to a computer program.   (Abstract & more)
  Abstract: Over recent decades there has been a growing interest in the question of whether computer programs are capable of genuinely creative activity. Although this notion can be explored as a purely philosophical debate, an alternative perspective is to consider what aspects of the behaviour of a program might be noted or measured in order to arrive at an empirically supported judgement that creativity has occurred. We sketch out, in general abstract terms, what goes on when a potentially creative program is constructed and run, and list some of the relationships (for example, between input and output) which might contribute to a decision about creativity. Specifically, we list a number of criteria which might indicate interesting properties of a program’s behaviour, from the perspective of possible creativity. We go on to review some ways in which these criteria have been applied to actual implementations, and some possible improvements to this way of assessing creativity
  Additional links for this entry:
  http://www.springerlink.com/content/873382581451wk27/fulltext.pdf
  http://www.springerlink.com/index/873382581451WK27.pdf
  http://www.ingentaconnect.com/content/klu/mind/2007/00000017/00000001/00009066
  
• E. Ronald & Moshe Sipper (2001). Intelligence is not enough: On the socialization of talking machines.   (Abstract & more)
  Abstract:   Since the introduction of the imitation game by Turing in 1950 there has been much debate as to its validity in ascertaining machine intelligence. We wish herein to consider a different issue altogether: granted that a computing machine passes the Turing Test, thereby earning the label of ``Turing Chatterbox'', would it then be of any use (to us humans)? From the examination of scenarios, we conclude that when machines begin to participate in social transactions, unresolved issues of trust and responsibility may well overshadow any raw reasoning ability they possess
  Additional links for this entry:
  http://books.google.com/books?hl=en&lr=&id=5BJaXSedqfIC&oi=fnd&pg=RA2-PA151&ots=rzjaYNDgnt&sig=3A-d8vteZ5VxcLftqerbTWdpGLI
  http://books.google.com/books?hl=en&lr=&id=ECj6fuEMdp0C&oi=fnd&pg=RA2-PA151&ots=blQIHqmec_&sig=7-0Vb2LD-6m2dlj8qK05keaxOEU
  http://www.springerlink.com/content/l363406154q21317/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=338896&PDF=1
  http://www.springerlink.com/index/L363406154Q21317.pdf
  http://www.ingentaconnect.com/content/klu/mind/2001/00000011/00000004/00338896
  
• C. T. A. Schmidt (2005). Of robots and believing.   (Abstract & more)
  Abstract: Discussion about the application of scientific knowledge in robotics in order to build people helpers is widespread. The issue herein addressed is philosophically poignant, that of robots that are “people”. It is currently popular to speak about robots and the image of Man. Behind this lurks the dialogical mind and the questions about the significance of an artificial version of it. Without intending to defend or refute the discourse in favour of ‘recreating’ Man, a lesser familiar question is brought forth: “and what if we were capable of creating a very convincible replica of man (constructing a robot-person), what would the consequences of this be and would we be satisfied with such technology?” Thorny topic; it questions the entire knowledge foundation upon which strong AI/Robotics is positioned. The author argues for improved monitoring of technological progress and thus favours implementing weaker techniques
  Additional links for this entry:
  http://www.springerlink.com/content/h605152238852292/fulltext.pdf
  http://www.springerlink.com/index/H605152238852292.pdf
  http://www.ingentaconnect.com/content/klu/mind/2005/00000015/00000002/00004734
  
• Bernd Carsten Stahl (2006). Responsible computers? A case for ascribing quasi-responsibility to computers independent of personhood or agency.   (Abstract & more)
  Abstract: There has been much debate whether computers can be responsible. This question is usually discussed in terms of personhood and personal characteristics, which a computer may or may not possess. If a computer fulfils the conditions required for agency or personhood, then it can be responsible; otherwise not. This paper suggests a different approach. An analysis of the concept of responsibility shows that it is a social construct of ascription which is only viable in certain social contexts and which serves particular social aims. If this is the main aspect of responsibility then the question whether computers can be responsible no longer hinges on the difficult problem of agency but on the possibly simpler question whether responsibility ascriptions to computers can fulfil social goals. The suggested solution to the question whether computers can be subjects of responsibility is the introduction of a new concept, called “quasi-responsibility” which will emphasise the social aim of responsibility ascription and which can be applied to computers
  Additional links for this entry:
  http://www.cse.dmu.ac.uk/~bstahl/publications/2006_responsible_computers_EIT.pdf
  http://www.springerlink.com/content/27607300gt85x46k/fulltext.pdf
  http://www.springerlink.com/index/27607300GT85X46K.pdf
  http://www.ingentaconnect.com/content/klu/etin/2006/00000008/00000004/00009112
  
• J. David Velleman (online). Artificial agency.   (Abstract & more)
  Abstract: I argue that participants in a virtual world such as "Second Life" exercise genuine agency via their avatars. Indeed, their avatars are fictional bodies with which they act in the virtual world, just as they act in the real world with their physical bodies. Hence their physical bodies can be regarded as their default avatars. I also discuss recent research into "believable" software agents, which are designed on principles borrowed from the character-based arts, especially cinematic animation as practiced by the artists at Disney and Warner Brothers Studios. I claim that these agents exemplify a kind of autonomy that should be of greater interest to philosophers than that exemplified by the generic agent modeled in current philosophical theory. The latter agent is autonomous by virtue of being governed by itself; but a believable agent appears to be governed by a self, which is the anima by which it appears to be animated. Putting these two discussions together, I suggest that philosophers of action should focus their attention on how we animate our bodies
  Additional links for this entry:
  http://phonline.org/paper.php?keynum=807
  http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1006884
  
• Mitchell Waldrop (1990). Can computers think?   (More)
• Rodrick Wallace (ms). New mathematical foundations for AI and alife: Are the necessary conditions for animal consciousness sufficient for the design of intelligent machines?   (Abstract & more)
  Abstract: Rodney Brooks' call for 'new mathematics' to revitalize the disciplines of artificial intelligence and artificial life can be answered by adaptation of what Adams has called 'the informational turn in philosophy', aided by the novel perspectives that program gives regarding empirical studies of animal cognition and consciousness. Going backward from the necessary conditions communication theory imposes on animal cognition and consciousness to sufficient conditions for machine design is, however, an extraordinarily difficult engineering task. The most likely use of the first generations of conscious machines will be to model the various forms of psychopathology, since we have little or no understanding of how consciousness is stabilized in humans or other animals
  Additional links for this entry:
  http://philsci-archive.pitt.edu/archive/00002646/01/alife.pdf
  
• Darren Whobrey (2001). Machine mentality and the nature of the ground relation.   (Abstract & more)
  Abstract:   John Searle distinguished between weak and strong artificial intelligence (AI). This essay discusses a third alternative, mild AI, according to which a machine may be capable of possessing a species of mentality. Using James Fetzer's conception of minds as semiotic systems, the possibility of what might be called ``mild AI'' receives consideration. Fetzer argues against strong AI by contending that digital machines lack the ground relationship required of semiotic systems. In this essay, the implementational nature of semiotic processes posited by Charles S. Peirce's triadic sign relation is re-examined in terms of the underlying dispositional processes and the ontological levels they would span in an inanimate machine. This suggests that, if non-human mentality can be replicated rather than merely simulated in a digital machine, the direction to pursue appears to be that of mild AI
  Additional links for this entry:
  http://www.mildai.org/papers/MAM2000-0-DJRW.pdf
  http://www.springerlink.com/content/tm143v51k2638028/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=323262&PDF=1
  http://www.springerlink.com/index/TM143V51K2638028.pdf
  http://www.ingentaconnect.com/content/klu/mind/2001/00000011/00000003/00323262
  

Computation and Representation

Symbols and Symbol Systems

• C. Franklin Boyle (2001). Transduction and degree of grounding.   (Abstract & more)
  Abstract: While I agree in general with Stevan Harnad's symbol grounding proposal, I do not believe "transduction" (or "analog process") PER SE is useful in distinguishing between what might best be described as different "degrees" of grounding and, hence, for determining whether a particular system might be capable of cognition. By 'degrees of grounding' I mean whether the effects of grounding go "all the way through" or not. Why is transduction limited in this regard? Because transduction is a physical process which does not speak to the issue of representation, and, therefore, does not explain HOW the informational aspects of signals impinging on sensory surfaces become embodied as symbols or HOW those symbols subsequently cause behavior, both of which, I believe, are important to grounding and to a system's cognitive capacity. Immunity to Searle's Chinese Room (CR) argument does not ensure that a particular system is cognitive, and whether or not a particular degree of groundedness enables a system to pass the Total Turing Test (TTT) may never be determined
  Additional links for this entry:
  http://cogsci.soton.ac.uk/~harnad/Temp/Think/boyle.htm
  http://cogsci.soton.ac.uk/~harnad/Papers/Harnad/harnad93.symb.anal.net.boyle.html
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad93.symb.anal.net.boyle.html
  
• Selmer Bringsjord (online). People are infinitary symbol systems: No sensorimotor capacity necessary.   (Abstract & more)
  Abstract: Stevan Harnad and I seem to be thinking about many of the same issues. Sometimes we agree, sometimes we don't; but I always find his reasoning refreshing, his positions sensible, and the problems with which he's concerned to be of central importance to cognitive science. His "Grounding Symbols in the Analog World with Neural Nets" (= GS) is no exception. And GS not only exemplifies Harnad's virtues, it also provides a springboard for diving into Harnad- Bringsjord terrain
  Additional links for this entry:
  http://psycprints.ecs.soton.ac.uk/archive/00000167/
  http://cogsci.soton.ac.uk/~harnad/Temp/Think/bringsj.htm
  http://cogsci.soton.ac.uk/~harnad/Papers/Harnad/harnad93.symb.anal.net.bringsjord.html
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad93.symb.anal.net.bringsjord.html
  http://psycprints.ecs.soton.ac.uk/archive/00000167/02/psyc.01.12.038.symbolism-connectionism.5.bringsjord
  http://psycprints.ecs.soton.ac.uk/archive/00000167/01/psyc.01.12.038.symbolism-connectionism.5.bringsjord.xml
  
• Andy Clark (2006). Material symbols.   (Abstract & more)
  Abstract: What is the relation between the material, conventional symbol structures that we encounter in the spoken and written word, and human thought? A common assumption, that structures a wide variety of otherwise competing views, is that the way in which these material, conventional symbol-structures do their work is by being translated into some kind of content-matching inner code. One alternative to this view is the tempting but thoroughly elusive idea that we somehow think in some natural language (such as English). In the present treatment I explore a third option, which I shall call the "complementarity" view of language. According to this third view the actual symbol structures of a given language add cognitive value by complementing (without being replicated by) the more basic modes of operation and representation endemic to the biological brain. The "cognitive bonus" that language brings is, on this model, not to be cashed out either via the ultimately mysterious notion of "thinking in a given natural language" or via some process of exhaustive translation into another inner code. Instead, we should try to think in terms of a kind of coordination dynamics in which the forms and structures of a language qua material symbol system play a key and irreducible role. Understanding language as a complementary cognitive resource is, I argue, an important part of the much larger project (sometimes glossed in terms of the "extended mind") of understanding human cognition as essentially and multiply hybrid: as involving a complex interplay between internal biological resources and external non-biological resources
  Additional links for this entry:
  http://www.psych.unito.it/csc/cogsci05/frame/talk/plen1-clark.pdf
  http://data.cstr.ed.ac.uk/internal/library/proceedings/2005/cogsci2005/docs/p1.pdf
  http://www.informaworld.com/smpp/./ftinterface~content=a747697830~fulltext=713240930
  http://taylorandfrancis.metapress.com/index/XNRG5M77H65766ML.pdf
  http://www.informaworld.com/index/747697830.pdf
  http://www.ingentaconnect.com/content/routledg/cphp/2006/00000019/00000003/art00002
  
• Stevan Harnad (1992). Connecting object to symbol in modeling cognition.   (Abstract & more)
  Abstract: Connectionism and computationalism are currently vying for hegemony in cognitive modeling. At first glance the opposition seems incoherent, because connectionism is itself computational, but the form of computationalism that has been the prime candidate for encoding the "language of thought" has been symbolic computationalism (Dietrich 1990, Fodor 1975, Harnad 1990c; Newell 1980; Pylyshyn 1984), whereas connectionism is nonsymbolic (Fodor & Pylyshyn 1988, or, as some have hopefully dubbed it, "subsymbolic" Smolensky 1988). This paper will examine what is and is not a symbol system. A hybrid nonsymbolic/symbolic system will be sketched in which the meanings of the symbols are grounded bottom-up in the system's capacity to discriminate and identify the objects they refer to. Neural nets are one possible mechanism for learning the invariants in the analog sensory projection on which successful categorization is based. "Categorical perception" (Harnad 1987a), in which similarity space is "warped" in the service of categorization, turns out to be exhibited by both people and nets, and may mediate the constraints exerted by the analog world of objects on the formal world of symbols
  Additional links for this entry:
  http://eprints.ecs.soton.ac.uk/3374/
  http://eprints.resist.ecs.soton.ac.uk/3374/
  http://cogprints.ecs.soton.ac.uk/archive/00001583/
  http://cogprints.org/1583/0/harnad92.symbol.object.html
  http://cogprints.org/1583/00/harnad92.symbol.object.html
  http://cogprints.soton.ac.uk/documents/disk0/00/00/15/83/
  http://cogsci.soton.ac.uk/~harnad/Papers/Harnad/harnad92.symbol.object.html
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad92.symbol.object.html
  http://eprints.ecs.soton.ac.uk/archive/00003374/02/harnad92.symbol.object.html
  http://citebase.eprints.org/cgi-bin/citations?id=oai:eprints.ecs.soton.ac.uk:3374
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:1583
  
• Stevan Harnad (2002). Symbol grounding and the origin of language.   (Abstract & more)
  Abstract: What language allows us to do is to "steal" categories quickly and effortlessly through hearsay instead of having to earn them the hard way, through risky and time-consuming sensorimotor "toil" (trial-and-error learning, guided by corrective feedback from the consequences of miscategorisation). To make such linguistic "theft" possible, however, some, at least, of the denoting symbols of language must first be grounded in categories that have been earned through sensorimotor toil (or else in categories that have already been "prepared" for us through Darwinian theft by the genes of our ancestors); it cannot be linguistic theft all the way down. The symbols that denote categories must be grounded in the capacity to sort, label and interact with the proximal sensorimotor projections of their distal category-members in a way that coheres systematically with their semantic interpretations, both for individual symbols, and for symbols strung together to express truth-value-bearing propositions
  Additional links for this entry:
  http://eprints.resist.ecs.soton.ac.uk/7714/
  http://eprints.resist.ecs.soton.ac.uk/6471/
  http://bi.snu.ac.kr/Courses/4ai05s/Essay/2-06.pdf
  http://cogprints.org/2133/00/harnad02.symlang.htm
  http://cogprints.ecs.soton.ac.uk/archive/00002133/
  http://cogprints.soton.ac.uk/documents/disk0/00/00/21/33/
  http://cogsci.soton.ac.uk/~harnad/Papers/Harnad/harnad02.symlang.htm
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad02.symlang.htm
  http://eprints.ecs.soton.ac.uk/archive/00007714/01/harnad02.symlang.htm
  http://eprints.ecs.soton.ac.uk/archive/00006471/01/harnad02.symlang.html
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:eprints.ecs.soton.ac.uk:7714
  
• Stevan Harnad (1993). Symbol grounding is an empirical problem: Neural nets are just a candidate component.   (Abstract & more)
  Abstract: "Symbol Grounding" is beginning to mean too many things to too many people. My own construal has always been simple: Cognition cannot be just computation, because computation is just the systematically interpretable manipulation of meaningless symbols, whereas the meanings of my thoughts don't depend on their interpretability or interpretation by someone else. On pain of infinite regress, then, symbol meanings must be grounded in something other than just their interpretability if they are to be candidates for what is going on in our heads. Neural nets may be one way to ground the names of concrete objects and events in the capacity to categorize them (by learning the invariants in their sensorimotor projections). These grounded elementary symbols could then be combined into symbol strings expressing propositions about more abstract categories. Grounding does not equal meaning, however, and does not solve any philosophical problems
  Additional links for this entry:
  http://eprints.resist.ecs.soton.ac.uk/3367/
  http://eprints.ecs.soton.ac.uk/archive/00003367/
  http://cogprints.org/1588/0/harnad93.cogsci.html
  http://cogprints.org/1588/00/harnad93.cogsci.html
  http://cogprints.ecs.soton.ac.uk/archive/00001588/
  http://cogprints.soton.ac.uk/documents/disk0/00/00/15/88/
  http://eprints.ecs.soton.ac.uk/3367/01/harnad93.cogsci.html
  http://cogprints.ecs.soton.ac.uk/documents/disk0/00/00/15/88/
  http://cogsci.soton.ac.uk/~harnad/Papers/Harnad/harnad93.cogsci.html
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad93.cogsci.html
  http://cogprints.ecs.soton.ac.uk/archive/00001588/00/harnad93.cogsci.html
  http://citebase.eprints.org/cgi-bin/citations?id=oai:eprints.ecs.soton.ac.uk:3367
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:1588
  
• Stevan Harnad (1990). The symbol grounding problem.   (Abstract & more)
  Abstract: There has been much discussion recently about the scope and limits of purely symbolic models of the mind and about the proper role of connectionism in cognitive modeling. This paper describes the symbol grounding problem: How can the semantic interpretation of a formal symbol system be made intrinsic to the system, rather than just parasitic on the meanings in our heads? How can the meanings of the meaningless symbol tokens, manipulated solely on the basis of their (arbitrary) shapes, be grounded in anything but other meaningless symbols? The problem is analogous to trying to learn Chinese from a Chinese/Chinese dictionary alone. A candidate solution is sketched: Symbolic representations must be grounded bottom-up in nonsymbolic representations of two kinds: (1) iconic representations, which are analogs of the proximal sensory projections of distal objects and events, and (2) categorical representations, which are learned and innate feature-detectors that pick out the invariant features of object and event categories from their sensory projections. Elementary symbols are the names of these object and event categories, assigned on the basis of their (nonsymbolic) categorical representations. Higher-order (3) symbolic representations, grounded in these elementary symbols, consist of symbol strings describing category membership relations (e.g., An X is a Y that is Z). Connectionism is one natural candidate for the mechanism that learns the invariant features underlying categorical representations, thereby connecting names to the proximal projections of the distal objects they stand for. In this way connectionism can be seen as a complementary component in a hybrid nonsymbolic/symbolic model of the mind, rather than a rival to purely symbolic modeling. Such a hybrid model would not have an autonomous symbolic module, however; the symbolic functions would emerge as an intrinsically dedicated symbol system as a consequence of the bottom-up grounding of categories' names in their sensory representations. Symbol manipulation would be governed not just by the arbitrary shapes of the symbol tokens, but by the nonarbitrary shapes of the icons and category invariants in which they are grounded
  Additional links for this entry:
  http://arxiv.org/abs/cs.AI/9906002
  http://eprints.resist.ecs.soton.ac.uk/8175/
  http://portal.acm.org/citation.cfm?id=96679
  http://cogprints.org/3106/1/sgproblem1.html
  http://cogprints.org/3106/01/sgproblem1.html
  http://citeseer.ist.psu.edu/harnad90symbol.html
  http://eprints.ecs.soton.ac.uk/archive/00008175/
  http://adsabs.harvard.edu/abs/1999cs........6002H
  http://www.ecs.soton.ac.uk/~harnad/Temp/symgro.htm
  http://cogprints.ecs.soton.ac.uk/archive/00003106/
  http://cogprints.soton.ac.uk/documents/disk0/00/00/06/15/
  http://cogprints.org/615/0/The_Symbol_Grounding_Problem.html
  http://cogprints.org/615/00/The_Symbol_Grounding_Problem.html
  http://www.isrl.uiuc.edu/~amag/langev/paper/harnad90theSymbol.html
  http://cogprints.ecs.soton.ac.uk/archive/00003106/01/sgproblem1.html
  http://cogsci.soton.ac.uk/~harnad/Papers/Harnad/harnad90.sgproblem.html
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad90.sgproblem.html
  http://wexler.free.fr/library/files/harnad (1990) the symbol grounding problem.pdf
  http://cogprints.ecs.soton.ac.uk/archive/00000615/00/The_Symbol_Grounding_Problem.html
  
• Karl F. MacDorman (1997). How to ground symbols adaptively.   (More)
• Allen Newell & Herbert A. Simon (1981). Computer science as empirical inquiry: Symbols and search.   (More)
  Additional links for this entry:
  http://portal.acm.org/citation.cfm?id=1283930
  http://www.jdl.ac.cn/turing/pdf/p113-newell.pdf
  http://portal.acm.org/citation.cfm?id=216000.216007
  http://home.dei.polimi.it/colombet/IA_2004/NewellandSimon.pdf
  http://www.elet.polimi.it/upload/colombet/IA_2004/NewellandSimon.pdf
  http://act-r.psy.cmu.edu/~douglass/Douglass/Agents/TopicPapers/PSSH/PSSH1.pdf
  http://act-r.psy.cmu.edu/people/douglass/Douglass/Agents/TopicPapers/PSSH/PSSH1.pdf
  http://www.phil.canterbury.ac.nz/tom_bestor/e-texts/Newell and Simon - CS as Empirical Inquiry (1975) p113-newell.pdf
  http://books.google.com/books?hl=en&lr=&id=UqhjMVwYKJsC&oi=fnd&pg=PA109&ots=E4xI7EhGQs&sig=JepEkCn93darsdPpvcGEn7VG61E
  http://books.google.com/books?hl=en&lr=&id=UqhjMVwYKJsC&oi=fnd&pg=PA109&ots=E4xIcIdzXt&sig=x8TqXd03sMF7Ku2tjTjKPLStp7M
  http://books.google.com/books?hl=en&lr=&id=UqhjMVwYKJsC&oi=fnd&pg=PA109&ots=E5oJfHgzVu&sig=5jb8G10Jz9vcHSA8SMjvAyDa79E
  http://books.google.com/books?hl=en&lr=&id=UqhjMVwYKJsC&oi=fnd&pg=PA109&ots=E5oKbHjCZv&sig=G4uV6cXYV2x1beYCw6nX6T4sbdI
  http://books.google.com/books?hl=en&lr=&id=UqhjMVwYKJsC&oi=fnd&pg=PA109&ots=E5oIdGczZr&sig=-ndDGHatiVA3bw4jwnF9OuPsYOE
  http://books.google.com/books?hl=en&lr=&id=UqhjMVwYKJsC&oi=fnd&pg=PA109&ots=E5oJ9HbFUs&sig=bj8ATdZXgK2geid62HIRWyOdnuo
  http://books.google.com/books?hl=en&lr=&id=UqhjMVwYKJsC&oi=fnd&pg=PA109&ots=E5oF7DeyQy&sig=cEaNBtdTsZioMpkk6W2Yd7_Ecf8
  http://books.google.com/books?hl=en&lr=&id=UqhjMVwYKJsC&oi=fnd&pg=PA109&ots=E5oFdDiBTr&sig=aHVuO1cvjfMeqsc-mx75yheObrA
  http://books.google.com/books?hl=en&lr=&id=UqhjMVwYKJsC&oi=fnd&pg=PA109&ots=E5oI7FhAWv&sig=TORphnvN5dYkzgzVFVGRZUaWdJc
  http://books.google.com/books?hl=en&lr=&id=UqhjMVwYKJsC&oi=fnd&pg=PA109&ots=E5oEbCjyVy&sig=NrAngS_FECgzGE2Iwqo6KD9OnDU
  http://books.google.com/books?hl=en&lr=&id=UqhjMVwYKJsC&oi=fnd&pg=PA109&ots=E4xIaIczSt&sig=YUwqrPXzwnaBIYgYiu0RVv1K52I
  http://books.google.com/books?hl=en&lr=&id=UqhjMVwYKJsC&oi=fnd&pg=PA109&ots=E5oHbFcCWw&sig=0Avl1AKiXUbrSFEGnL7r0e8A8bM
  http://books.google.com/books?hl=en&lr=&id=UqhjMVwYKJsC&oi=fnd&pg=PA109&ots=E5oG9EdDXt&sig=43O3YB2BeYIwnOoSeJ-LE-V8lao
  http://books.google.com/books?hl=en&lr=&id=UqhjMVwYKJsC&oi=fnd&pg=PA109&ots=E5oGfEiFSy&sig=uTVh7cE69OpNBo9FxMib124gZ00
  
• Allen Newell (1980). Physical symbol systems.   (More)
  Additional links for this entry:
  http://www.leaonline.com/doi/pdf/10.1207/s15516709cog0402_2
  http://www.leaonline.com/doi/pdfplus/10.1207/s15516709cog0402_2
  http://www.cogsci.rpi.edu/CSJarchive/1980v04/i02/p0135p0183/MAIN.PDF
  http://stinet.dtic.mil/oai/oai?verb=getRecord&metadataPrefix=html&identifier=ADA224247
  
• Steven Pinker (2004). Why nature & nurture won't go away.   (More)
  Additional links for this entry:
  http://www.mitpressjournals.org/doi/abs/10.1162/0011526042365591
  http://pinker.wjh.harvard.edu/articles/papers/nature_nurture.pdf
  http://pinker.wjh.harvard.edu/articles/papers/nature_nurture.pdf
  http://mitpress.mit.edu/catalog/item/default.asp?tid=17270&ttype=6
  http://mitpress.mit.edu/catalog/item/default.asp?ttype=6&tid=17270
  http://www.mitpressjournals.org/doi/pdfplus/10.1162/0011526042365591
  http://www.ingentaconnect.com/content/mitpress/dae/2004/00000133/00000004/art00001
  
• Herbert L. Roitblat (2001). Computational grounding.   (Abstract & more)
  Abstract: Harnad defines computation to mean the manipulation of physical symbol tokens on the basis of syntactic rules defined over the shapes of the symbols, independent of what, if anything, those symbols represent. He is, of course, free to define terms in any way that he chooses, and he is very clear about what he means by computation, but I am uncomfortable with this definition. It excludes, at least at a functional level of description, much of what a computer is actually used for, and much of what the brain/mind does. When I toss a Frisbee to the neighbor's dog, the dog does not, I think, engage in a symbolic soliloquy about the trajectory of the disc, the wind's effects on it, and formulas for including lift and the acceleration due to gravity. There are symbolic formulas for each of these relations, but the dog insofar as I can tell, does not use any of these formulas. Nevertheless, it computes these factors in order to intercept the disc in the air. I argue that determining the solution to a differential equation is at least as much computation as is processing symbols. The disagreement is over what counts as computation, I think that Harnad and I both agree that the dog solves the trajectory problem implicitly. This definition is important, because, although Harnad offers a technical definition for what he means by computation, the folk- definition of the term is probably interpreted differently, and I believe this leads to trouble
  Additional links for this entry:
  http://www.ecs.soton.ac.uk/~harnad/Papers/Harnad/harnad93.symb.anal.net.roitblat.html
  
• Susan Schneider (forthcoming). The nature of primitive symbols in the language of thought.   (Abstract & more)
  Abstract: This paper provides a theory of the nature of symbols in the language of thought (LOT). My discussion consists in three parts. In part one, I provide three arguments for the individuation of primitive symbols in terms of total computational role. The first of these arguments claims that Classicism requires that primitive symbols be typed in this manner; no other theory of typing will suffice. The second argument contends that without this manner of symbol individuation, there will be computational processes that fail to supervene on syntax, together with the rules of composition and the computational algorithms. The third argument says that cognitive science needs a natural kind that is typed by total computational role. Otherwise, either cognitive science will be incomplete, or its laws will have counterexamples. Then, part two defends this view from a criticism, offered by both Jerry Fodor and Jesse Prinz, who respond to my view with the charge that because the types themselves are individuated
  Additional links for this entry:
  http://www.sas.upenn.edu/~sls/documents/SchneiderNatureSymbolsMindLang.doc
  http://www.sas.upenn.edu/~sls/documents/SchneiderNatureSymbolsMindLang-1-2.pdf
  
• Ron Sun (2000). Symbol grounding: A new look at an old idea.   (Abstract & more)
  Abstract: Symbols should be grounded, as has been argued before. But we insist that they should be grounded not only in subsymbolic activities, but also in the interaction between the agent and the world. The point is that concepts are not formed in isolation (from the world), in abstraction, or "objectively." They are formed in relation to the experience of agents, through their perceptual/motor apparatuses, in their world and linked to their goals and actions. This paper takes a detailed look at this relatively old issue, with a new perspective, aided by our work of computational cognitive model development. To further our understanding, we also go back in time to link up with earlier philosophical theories related to this issue. The result is an account that extends from computational mechanisms to philosophical abstractions
  Additional links for this entry:
  http://www.cogsci.rpi.edu/~rsun/sun.PP00.ps
  http://citeseer.ist.psu.edu/sun99symbol.html
  http://www.informaworld.com/smpp/./ftinterface~content=a713690432~fulltext=713240930
  http://taylorandfrancis.metapress.com/index/KKLQAQTYVG4RUY7G.pdf
  http://www.informaworld.com/index/KKLQAQTYVG4RUY7G.pdf
  http://www.ingentaconnect.com/content/routledg/cphp/2000/00000013/00000002/art00001
  
• Mariarosaria Taddeo & Luciano Floridi (2008). A praxical solution of the symbol grounding problem.   (Abstract & more)
  Abstract: This article is the second step in our research into the Symbol Grounding Problem (SGP). In a previous work, we defined the main condition that must be satisfied by any strategy in order to provide a valid solution to the SGP, namely the zero semantic commitment condition (Z condition). We then showed that all the main strategies proposed so far fail to satisfy the Z condition, although they provide several important lessons to be followed by any new proposal. Here, we develop a new solution of the SGP. It is called praxical in order to stress the key role played by the interactions between the agents and their environment. It is based on a new theory of meaning—Action-based Semantics (AbS)—and on a new kind of artificial agents, called two-machine artificial agents (AM²). Thanks to their architecture, AM2s implement AbS, and this allows them to ground their symbols semantically and to develop some fairly advanced semantic abilities, including the development of semantically grounded communication and the elaboration of representations, while still respecting the Z condition
  Additional links for this entry:
  http://www.springerlink.com/content/f748ru5636784058/fulltext.pdf
  
• Evan Thompson (1997). Symbol grounding: A bridge from artificial life to artificial intelligence.   (Abstract & more)
  Abstract: This paper develops a bridge from AL issues about the symbol–matter relation to AI issues about symbol-grounding by focusing on the concepts of formality and syntactic interpretability. Using the DNA triplet-amino acid specification relation as a paradigm, it is argued that syntactic properties can be grounded as high-level features of the non-syntactic interactions in a physical dynamical system. This argu- ment provides the basis for a rebuttal of John Searle’s recent assertion that syntax is observer-relative (1990, 1992). But the argument as developed also challenges the classic symbol-processing theory of mind against which Searle is arguing, as well as the strong AL thesis that life is realizable in a purely computational medium. Finally, it provides a new line of support for the autonomous systems approach in AL and AI (Varela & Bourgine 1992a, 1992b). © 1997 Academic Press
  Additional links for this entry:
  http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=9209755&dopt=Citation
  http://www.ingentaconnect.com/content/ap/br/1997/00000034/00000001/art00906
  

Computational Semantics

• Varol Akman (1998). Situations and artificial intelligence.   (More)
• Radu J. Bogdan (1994). By way of means and ends.   (Abstract & more)
  Abstract: This chapter provides the teleological foundations for our analysis of guidance to goal. Its objective is to ground goal-directedness genetically. The basic suggestion is this. Organisms are small things, with few energy resources and puny physical means, battling a ruthless physical and biological nature. How do they manage to survive and multiply? CLEVERLY, BY ORGANIZING
• Daniel C. Dennett (2003). The Baldwin Effect: A Crane, Not a Skyhook.   (Abstract & more)
  Abstract: In 1991, I included a brief discussion of the Baldwin effect in my account of the evolution of human consciousness, thinking I was introducing to non-specialist readers a little-appreciated, but no longer controversial, wrinkle in orthodox neo-Darwinism. I had thought that Hinton and Nowlan (1987) and Maynard Smith (1987) had shown clearly and succinctly how and why it worked, and restored the neglected concept to grace. Here is how I put it then
  Additional links for this entry:
  http://ase.tufts.edu/cogstud/papers/baldwincranefin.htm
  http://books.google.com/books?hl=en&lr=&id=yBtRzBilw1MC&oi=fnd&pg=PA69&dq=The+Baldwin+effect+Dennett&ots=2I8w0wd3n_&sig=urmY-aQvjQsgpb_W81dI6SjJvGc
  
• Jerry A. Fodor (1978). Tom swift and his procedural grandmother.   (More)
• Stevan Harnad (2002). Darwin, Skinner, Turing and the mind.   (Abstract & more)
  Abstract: Darwin differs from Newton and Einstein in that his ideas do not require a complicated or deep mind to understand them, and perhaps did not even require such a mind in order to generate them in the first place. It can be explained to any school-child (as Newtonian mechanics and Einsteinian relativity cannot) that living creatures are just Darwinian survival/reproduction machines. They have whatever structure they have through a combination of chance and its consequences: Chance causes changes in the genetic blueprint from which organisms' bodies are built, and if those changes are more successful in helping their owners survive and reproduce than their predecessors or their rivals, then, by definition, those changes are reproduced, and thereby become more prevalent in succeeding generations: Whatever survives/reproduces better survives/reproduces better. That is the tautological force that shaped us
  Additional links for this entry:
  http://cogprints.org/3016/01/darwin.htm
  http://cogprints.org/3016/01/darwin.htm
  http://eprints.resist.ecs.soton.ac.uk/7715/
  http://eprints.ecs.soton.ac.uk/7715/01/darwin.htm
  http://www.ecs.soton.ac.uk/~harnad/Temp/darwin.htm
  http://cogprints.ecs.soton.ac.uk/archive/00003016/
  http://eprints.ecs.soton.ac.uk/7715/01/darwin.htm
  http://www.ecs.soton.ac.uk/~harnad/Temp/darwin.htm
  http://cogprints.ecs.soton.ac.uk/archive/00003016/
  http://citebase.eprints.org/cgi-bin/citations?id=oai:cogprints.soton.ac.uk:3016
  http://citebase.eprints.org/cgi-bin/citations?id=oai:cogprints.soton.ac.uk:3016
  http://citebase.eprints.org/cgi-bin/citations?id=oai:eprints.ecs.soton.ac.uk:7715
  
• Philip N. Johnson-Laird (1977). Procedural semantics.   (More)
• Drew McDermott (1978). Tarskian semantics, or no notation without denotation.   (More)
  Additional links for this entry:
  http://www.leaonline.com/doi/abs/10.1207/s15516709cog0203_5
  http://www.leaonline.com/doi/pdf/10.1207/s15516709cog0203_5
  http://www.leaonline.com/doi/pdfplus/10.1207/s15516709cog0203_5
  
• David Papineau (2006). The cultural origins of cognitive adaptations.   (Abstract & more)
  Abstract: According to an influential view in contemporary cognitive science, many human cognitive capacities are innate. The primary support for this view comes from ‘poverty of stimulus’ arguments. In general outline, such arguments contrast the meagre informational input to cognitive development with its rich informational output. Consider the ease with which humans acquire languages, become facile at attributing psychological states (‘folk psychology’), gain knowledge of biological kinds (‘folk biology’), or come to understand basic physical processes (‘folk physics’). In all these cases, the evidence available to a growing child is far too thin and noisy for it to be plausible that the underlying principles involved are derived from general learning mechanisms. This only alternative hypothesis seems to be that the child’s grasp of these principles is innate. (Cf. Laurence and Margolis, 2001.)
  Additional links for this entry:
  http://journals.cambridge.org/abstract_S1358246105056134
  
• William J. Rapaport (1995). Understanding understanding: Syntactic semantics and computational cognition.   (More)
  Additional links for this entry:
  http://www.cse.buffalo.edu/~rapaport/Papers/understanding.ps
  http://historical.ncstrl.org/litesite-data/suny_buffalo_cs/94-28.ps.Z
  http://links.jstor.org/sici?sici=1520-8583(1995)9<49:UUSSAC>2.0.CO;2-G
  http://www.jstor.org/sici?sici=1520-8583(1995)9<49:UUSSAC>2.0.CO;2-G
  http://www.jstor.org/stable/pdfplus/2214212.pdf
  
• B. Smith (1988). On the semantics of clocks.   (More)
• Erkan Tin & Varol Akman (1994). Computational situation theory.   (Abstract & more)
  Abstract: Situation theory has been developed over the last decade and various versions of the theory have been applied to a number of linguistic issues. However, not much work has been done in regard to its computational aspects. In this paper, we review the existing approaches towards `computational situation theory' with considerable emphasis on our own research
  Additional links for this entry:
  http://cogprints.org/200/0/sig.ps
  http://citeseer.ist.psu.edu/599996.html
  http://cogprints.ecs.soton.ac.uk/archive/00000200/
  http://portal.acm.org/citation.cfm?id=191604.191608
  http://citeseer.ist.psu.edu/tin94computational.html
  http://www.cs.bilkent.edu.tr/~akman/jour-papers/sigart/sigart1994.pdf
  http://citebase.eprints.org/cgi-bin/citations?id=oai:cogprints.soton.ac.uk:200
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:200
  
• W. Woods (1981). Procedural semantics as a theory of meaning.   (More)

Implicit/Explicit Rules and Representations

• William P. Bechtel (forthcoming). Explanation: Mechanism, modularity, and situated cognition.   (Abstract & more)
  Abstract: The situated cognition movement has emerged in recent decades (although it has roots in psychologists working earlier in the 20^th century including Vygotsky, Bartlett, and Dewey) largely in reaction to an approach to explaining cognition that tended to ignore the context in which cognitive activities typically occur. Fodor’s (1980) account of the research strategy of methodological solipsism, according to which only representational states within the mind are viewed as playing causal roles in producing cognitive activity, is an extreme characterization of this approach. (As Keith Gunderson memorably commented when Fodor first presented this characterization, it amounts to reversing behaviorism by construing the mind as a white box in a black world). Critics as far back as the 1970s and 1980s objected to many experimental paradigms in cognitive psychology as not being ecologically valid; that is, they maintained that the findings only applied to the artificial circumstances created in the laboratory and did not generalize to real world settings (Neisser, 1976; 1987). The situated cognition movement, however, goes much further than demanding ecologically valid experiments—it insists that an agent’s cognitive activities are inherently embedded and supported by dynamic interactions with the agent’s body and features of its environment
• Andy Clark (1991). In defense of explicit rules.   (More)
• Daniel C. Dennett (1993). Review of F. Varela, E. Thompson and E. Rosch, The Embodied Mind.   (Abstract & more)
  Abstract: Cognitive science, as an interdisciplinary school of thought, may have recently moved beyond the bandwagon stage onto the throne of orthodoxy, but it does not make a favorable first impression on many people. Familiar reactions on first encounters range from revulsion to condescending dismissal--very few faces in the crowd light up with the sense of "Aha! So that's how the mind works! Of course!" Cognitive science leaves something out, it seems; moreover, what it apparently leaves out is important, even precious. Boiled down to its essence, cognitive science proclaims that in one way or another our minds are computers, and this seems so mechanistic, reductionistic, intellectualistic, dry, philistine, unbiological. It leaves out emotion, or what philosophers call qualia, or value, or mattering, or . . . the soul. It doesn't explain what minds are so much as attempt to explain minds away
  Additional links for this entry:
  http://ase.tufts.edu/cogstud/papers/varela.htm
  http://cogprints.ecs.soton.ac.uk/archive/00000273/
  http://citebase.eprints.org/cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:273
  
• Robert F. Hadley (1995). The 'explicit-implicit' distinction.   (Abstract & more)
  Abstract:   Much of traditional AI exemplifies the explicit representation paradigm, and during the late 1980''s a heated debate arose between the classical and connectionist camps as to whether beliefs and rules receive an explicit or implicit representation in human cognition. In a recent paper, Kirsh (1990) questions the coherence of the fundamental distinction underlying this debate. He argues that our basic intuitions concerning explicit and implicit representations are not only confused but inconsistent. Ultimately, Kirsh proposes a new formulation of the distinction, based upon the criterion ofconstant time processing.The present paper examines Kirsh''s claims. It is argued that Kirsh fails to demonstrate that our usage of explicit and implicit is seriously confused or inconsistent. Furthermore, it is argued that Kirsh''s new formulation of the explicit-implicit distinction is excessively stringent, in that it banishes virtually all sentences of natural language from the realm of explicit representation. By contrast, the present paper proposes definitions for explicit and implicit which preserve most of our strong intuitions concerning straightforward uses of these terms. It is also argued that the distinction delineated here sustains the meaningfulness of the abovementioned debate between classicists and connectionists
  Additional links for this entry:
  http://www.springerlink.com/content/content/kl736k107182317h/fulltext.pdf
  http://www.springerlink.com/content/kl736k107182317h/fulltext.pdf
  http://www.springerlink.com/index/KL736K107182317H.pdf
  
• Fernando Martínez & Jesús Ezquerro Martínez (1998). Explicitness with psychological ground.   (Abstract & more)
  Abstract:   Explicitness has usually been approached from two points of view, labelled by Kirsh the structural and the process view, that hold opposite assumptions to determine when information is explicit. In this paper, we offer an intermediate view that retains intuitions from both of them. We establish three conditions for explicit information that preserve a structural requirement, and a notion of explicitness as a continuous dimension. A problem with the former accounts was their disconnection with psychological work on the issue. We review studies by Karmiloff-Smith, and Shanks and St. John to show that the proposed conditions have psychological grounds. Finally, we examine the problem of explicit rules in connectionist systems in the light of our framework
  Additional links for this entry:
  http://www.csa.com/partners/viewrecord.php?requester=gs&collection=TRD&recid=381463CI
  http://www.springerlink.com/content/j4u0011h11660267/fulltext.pdf
  http://www.springerlink.com/index/J4U0011H11660267.pdf
  http://www.ingentaconnect.com/content/klu/mind/1998/00000008/00000003/00160303
  
• Lawrence A. Shapiro (ms). The embodied cognition research program.   (Abstract & more)
  Abstract: Unifying traditional cognitive science is the idea that thinking is a process of symbol manipulation, where symbols lead both a syntactic and a semantic life. The syntax of a symbol comprises those properties in virtue of which the symbol undergoes rule-dictated transformations. The semantics of a symbol constitute the symbolsÕ meaning or representational content. Thought consists in the syntactically determined manipulation of symbols, but in a way that respects their semantics. Thus, for instance, a calculating computer sensitive only to the shape of symbols might produce the symbol Ô5Õ in response to the inputs Ô2Õ, Ô+Õ, and Ô3Õ. As far as the computer is concerned, these symbols have no meaning, but because of its program it will produce outputs that, to the user, Òmake senseÓ given the meanings the user attributes to the symbols
  Additional links for this entry:
  http://philosophy.wisc.edu/shapiro/HomePage/PhilComp.htm
  http://philosophy.wisc.edu/shapiro/HomePage/embodiedcognition.pdf
  
• Paul G. Skokowski (1994). Can computers carry content "inexplicitly"?   (Abstract & more)
  Abstract:   I examine whether it is possible for content relevant to a computer''s behavior to be carried without an explicit internal representation. I consider three approaches. First, an example of a chess playing computer carrying emergent content is offered from Dennett. Next I examine Cummins response to this example. Cummins says Dennett''s computer executes a rule which is inexplicitly represented. Cummins describes a process wherein a computer interprets explicit rules in its program, implements them to form a chess-playing device, then this device executes the rules in a way that exhibits them inexplicitly. Though this approach is intriguing, I argue that the chess-playing device cannot exist as imagined. The processes of interpretation and implementation produce explicit representations of the content claimed to be inexplicit. Finally, the Chinese Room argument is examined and shown not to save the notion of inexplicit information. This means the strategy of attributing inexplicit content to a computer which is executing a rule, fails
  Additional links for this entry:
  http://www.csa.com/partners/viewrecord.php?requester=gs&collection=TRD&recid=0148099CI
  http://www.springerlink.com/content/j821320368ht5863/fulltext.pdf
  http://www.springerlink.com/index/J821320368HT5863.pdf
  
• Peter Slezak (1999). Situated cognition.   (Abstract & more)
  Abstract: The self-advertising, at least, suggests that 'situated cognition' involves the most fundamental conceptual re-organization in AI and cognitive science, even appearing to deny that cognition is to be explained by mental representations. In their defence of the orthodox symbolic representational theory, A. Vera and H. Simon (1993) have rebutted many of these claims, but they overlook an important reading of situated arguments which may, after all, involve a revolutionary insight. I show that the whole debate turns on puzzles familiar from the history of philosophy and psychology and these may serve to clarify the current disputes
• John Sutton (2000). The body and the brain.   (Abstract & more)
  Abstract: Does self?knowledge help? A rationalist, presumably, thinks that it does: both tha