Compiled by David Chalmers (Editor) and David Bourget (Assistant Editor), Australian National University. Part of MindPapers. Suggest an entry.

Javascript Menu by Deluxe-Menu.com		All fields Surname Advanced
		click here for help on how to search

Search tips

There are three kinds of search you can perform:

All fields

This mode searches for entries containing all the entered words in their title, author, date, comment field, or in any of many other fields showing on MindPapers pages.

Surname

This mode searches for entries containing the text string you entered in their author field. Note that the database does not have first names for all authors, so it is preferable to search only by surnames. If you search for a full name or a name with an initial, enter it in the format used internally by MindPapers, namely the "Lastname, Firstname" or "Lastname, F." format.

Advanced

This mode differs from the all fields mode in two respects. First, some information not publicly available on MindPapers is searched, e.g., abstracts and excerpts gathered by the MindPapers crawler, which are not always accurate but can help broaden one's search. Second, you may prefix any term with a '+' or '-' to narrow the search to entries containing it or not containing it, respectively. Terms which are not prefixed by a '+' are not mandatory. Instead, they are weighed depending on their frequency in order to determine the best search results. You may also search for a literal string composed of several words by putting them in double quotation marks (").

Note that short and / or common words are ignored by the search engine.

Try MindPapers to find published items which are available on a subscription basis.

close help

Philosophy of artificial intelligence :: Philosophy of connectionism :: Representation in connectionism

• William Bechtel (1994). Natural deduction in connectionist systems.   (Abstract & more)
  Abstract:   The relation between logic and thought has long been controversial, but has recently influenced theorizing about the nature of mental processes in cognitive science. One prominent tradition argues that to explain the systematicity of thought we must posit syntactically structured representations inside the cognitive system which can be operated upon by structure sensitive rules similar to those employed in systems of natural deduction. I have argued elsewhere that the systematicity of human thought might better be explained as resulting from the fact that we have learned natural languages which are themselves syntactically structured. According to this view, symbols of natural language are external to the cognitive processing system and what the cognitive system must learn to do is produce and comprehend such symbols. In this paper I pursue that idea by arguing that ability in natural deduction itself may rely on pattern recognition abilities that enable us to operate on external symbols rather than encodings of rules that might be applied to internal representations. To support this suggestion, I present a series of experiments with connectionist networks that have been trained to construct simple natural deductions in sentential logic. These networks not only succeed in reconstructing the derivations on which they have been trained, but in constructing new derivations that are only similar to the ones on which they have been trained
  Additional links for this entry:
  http://citeseer.ist.psu.edu/bechtel94natural.html
  http://www.blutner.de/NeuralNets/Texts/DERIVATI.pdf
  http://mechanism.ucsd.edu/~bill/research/DERIVATI.pdf
  http://amor.rz.hu-berlin.de/~h0998dgh/NeuralNets/Texts/DERIVATI.pdf
  http://amor.cms.hu-berlin.de/~h0998dgh/NeuralNets/Texts/DERIVATI.pdf
  http://www.springerlink.com/content/q71158t2342jl517/fulltext.pdf
  http://www.springerlink.com/index/Q71158T2342JL517.pdf
  
• Keith Butler (1995). Representation and computation in a deflationary assessment of connectionist cognitive science.   (Abstract & more)
  Abstract:   Connectionism provides hope for unifying work in neuroscience, computer science, and cognitive psychology. This promise has met with some resistance from Classical Computionalists, which may have inspired Connectionists to retaliate with bold, inflationary claims on behalf of Connectionist models. This paper demonstrates, by examining three intimately connected issues, that these inflationary claims made on behalf of Connectionism are wrong. This should not be construed as an attack on Connectionism, however, since the inflated claims made on its behalf have the look of cures for which there are no ailments. There is nothing wrong with Connectionism for its failure to solve illusory problems
  Additional links for this entry:
  http://www.springerlink.com/content/r347125074346147/fulltext.pdf
  http://www.springerlink.com/index/R347125074346147.pdf
  
• Andy Clark (ms). Connectionism, nonconceptual content, and representational redescription.   (More)
• Robert Cummins (1991). The role of representation in connectionist explanation of cognitive capacities.   (More)
• Adrian Cussins (1990). The connectionist construction of concepts.   (Abstract & more)
  Abstract: The character of computational modelling of cognition depends on an underlying theory of representation. Classical cognitive science has exploited the syntax/semantics theory of representation that derives from logic. But this has had the consequence that the kind of psychological explanation supported by classical cognitive science is

  _conceptualist_:

  psychological phenomena are modelled in terms of relations that hold between concepts, and between the sensors/effectors and concepts. This kind of explanation is inappropriate for the Proper Treatment of Connectionism (Smolensky 1988)
  Additional links for this entry:
  http://www.haecceia.com/FILES/c3_kings_london.htm
  
• Chris Eliasmith (online). Structure without symbols: Providing a distributed account of high-level cognition.   (Abstract & more)
  Abstract: There has been a long-standing debate between symbolicists and connectionists concerning the nature of representation used by human cognizers. In general, symbolicist commitments have allowed them to provide superior models of high-level cognitive function. In contrast, connectionist distributed representations are preferred for providing a description of low-level cognition. The development of Holographic Reduced Representations (HRRs) has opened the possibility of one representational medium unifying both low-level and high-level descriptions of cognition. This paper describes the relative strengths and weaknesses of symbolic and distributed representations. HRRs are shown to capture the important strengths of both types of representation. These properties of HRRs allow a rebuttal of Fodor and McLaughlin's (1990) criticism that distributed representations are not adequately structure sensitive to provide a full account of human cognition
• Robert Hadley (2004). On the proper treatment of semantic systematicity.   (Abstract & more)
  Abstract:   The past decade has witnessed the emergence of a novel stance on semantic representation, and its relationship to context sensitivity. Connectionist-minded philosophers, including Clark and van Gelder, have espoused the merits of viewing hidden-layer, context-sensitive representations as possessing semantic content, where this content is partially revealed via the representations'' position in vector space. In recent work, Bodén and Niklasson have incorporated a variant of this view of semantics within their conception of semantic systematicity. Moreover, Bodén and Niklasson contend that they have produced experimental results which not only satisfy a kind of context-based, semantic systematicity, but which, to the degree that reality permits, effectively deals with challenges posed by Fodor and Pylyshyn (1988), and Hadley (1994a). The latter challenge involved well-defined criteria for strong semantic systematicity. This paper examines the relevant claims and experiments of Bodén and Niklasson. It is argued that their case fatally involves two fallacies of equivocation; one concerning ''semantic content'' and the other concerning ''novel test sentences''. In addition, it is argued that their ultimate construal of context sensitive semantics contains serious confusions. These confusions are also found in certain publications dealing with "latent semantic analysis". Thus, criticisms presented here have relevance beyond the work of Bodén and Niklasson
  Additional links for this entry:
  http://portal.acm.org/citation.cfm?id=976702.976735
  http://www.ingentaconnect.com/content/klu/mind/2004/00000014/00000002/05142070
  http://www.springerlink.com/content/p4312417q27100p0/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=5142070&PDF=1
  http://www.springerlink.com/index/P4312417Q27100P0.pdf
  
• W. F. G. Haselager (1999). On the potential of non-classical constituency.   (More)
  Additional links for this entry:
  http://www.nici.kun.nl/~haselag/publications/1999c.pdf
  http://www.socsci.kun.nl/~haselag/publications/1999c.pdf
  http://www.nici.ru.nl/~haselag/publications/NonClassConst99.pdf
  http://www.nici.kun.nl/~haselag/publications/NonClassConst99.pdf
  http://www.socsci.kun.nl/~haselag/publications/NonClassConst99.pdf
  
• Daniel Haybron (2000). The causal and explanatory role of information stored in connectionist networks.   (Abstract & more)
  Abstract:   In this paper I defend the propriety of explaining the behavior of distributed connectionist networks by appeal to selected data stored therein. In particular, I argue that if there is a problem with such explanations, it is a consequence of the fact that information storage in networks is superpositional, and not because it is distributed. I then develop a ``proto-account'''' of causation for networks, based on an account of Andy Clark''s, that shows even superpositionality does not undermine information-based explanation. Finally, I argue that the resulting explanations are genuinely informative and not vacuous
  Additional links for this entry:
  http://www.slu.edu/~haybrond/Connectionist information storage.pdf
  http://www.slu.edu/users/users/haybrond/Connectionist information storage.pdf
  http://www.slu.edu/users/users/haybrond/Connectionist information storage.pdf
  http://www.csa.com/partners/viewrecord.php?requester=gs&collection=TRD&recid=536479CI
  http://www.ingentaconnect.com/content/klu/mind/2000/00000010/00000003/00258827
  http://www.springerlink.com/content/content/t061056966k44051/fulltext.pdf
  http://www.springerlink.com/content/t061056966k44051/fulltext.pdf
  http://www.kluweronline.com/article.asp?PIPS=258827&PDF=1
  http://www.springerlink.com/index/T061056966K44051.pdf
  
• Aarre Laakso & Garrison Cottrell (2000). Content and cluster analysis: Assessing representational similarity in neural systems.   (Abstract & more)
  Abstract: If connectionism is to be an adequate theory of mind, we must have a theory of representation for neural networks that allows for individual differences in weighting and architecture while preserving sameness, or at least similarity, of content. In this paper we propose a procedure for measuring sameness of content of neural representations. We argue that the correct way to compare neural representations is through analysis of the distances between neural activations, and we present a method for doing so. We then use the technique to demonstrate empirically that different artificial neural networks trained by backpropagation on the same categorization task, even with different representational encodings of the input patterns and different numbers of hidden units, reach states in which representations at the hidden units are similar. We discuss how this work provides a rebuttal to Fodor and Lepore's critique of Paul Churchland's state space semantics
  Additional links for this entry:
  http://www.laakshmi.com/aarre/cv/phipsy.pdf
  http://www.cs.ucsd.edu/groups/guru/docs/laakso2000.pdf
  http://www-cse.ucsd.edu/groups/guru/docs/laakso2000.pdf
  http://www.cse.ucsd.edu/groups/guru/docs/laakso2000.pdf
  http://www.informaworld.com/smpp/./ftinterface~content=a713690421~fulltext=713240930
  http://www.ingentaconnect.com/content/routledg/cphp/2000/00000013/00000001/art00002
  http://taylorandfrancis.metapress.com/index/RY0JBTH3PY9B6GF2.pdf
  http://www.informaworld.com/index/RY0JBTH3PY9B6GF2.pdf
  
• Eric Lormand (ms). Connectionist content.   (More)
• Gerard O'Brien (1989). Connectionism, analogicity and mental content.   (More)
• Gerard O'Brien & Jonathan Opie (2004). Notes toward a structuralist theory of mental representation.   (Abstract & more)
  Abstract: Any creature that must move around in its environment to find nutrients and mates, in order to survive and reproduce, faces the problem of sensorimotor control. A solution to this problem requires an on-board control mechanism that can shape the creature’s behaviour so as to render it “appropriate” to the conditions that obtain. There are at least three ways in which such a control mechanism can work, and Nature has exploited them all. The first and most basic way is for a creature to bump into the things in its environment, and then, depending on what has been encountered, seek to modify its behaviour accordingly. Such an approach is risky, however, since some things in the environment are distinctly unfriendly. A second and better way, therefore, is for a creature to exploit ambient forms of energy that carry information about the distal structure of the environment. This is an improvement on the first method since it enables the creature to respond to the surroundings without actually bumping into anything. Nonetheless, this second method also has its limitations, one of which is that the information conveyed by such ambient energy is often impoverished, ambiguous and intermittent
• William Ramsey (1997). Do connectionist representations earn their explanatory keep?   (More)
  Additional links for this entry:
  http://www.ingentaconnect.com/content/bpl/mila/1997/00000012/00000001/art00035
  http://www.ingentaconnect.com/content/bpl/mila/1997/00000012/00000001/art00003
  http://www.blackwell-synergy.com/doi/abs/10.1111/1468-0017.00035
  
• Joop Schopman & A. Shawky (1999). Remarks on the impact of connectionism on our thinking about concepts.   (More)
• Tony Stone & Martin Davies (2000). Autonomous psychology and the moderate neuron doctrine.   (Abstract & more)
  Abstract: _Two notions of autonomy are distinguished. The respective_ _denials that psychology is autonomous from neurobiology are neuron_ _doctrines, moderate and radical. According to the moderate neuron_ _doctrine, inter-disciplinary interaction need not aim at reduction. It is_ _proposed that it is more plausible that there is slippage from the_ _moderate to the radical neuron doctrine than that there is confusion_ _between the radical neuron doctrine and the trivial version._
  Additional links for this entry:
  http://philrsss.anu.edu.au/~mdavies/papers/aut.pdf
  http://www.journals.cambridge.org/abstract_S0140525X99452197
  http://www.journals.cambridge.org/abstract_S0140525X99452197
  http://journals.cambridge.org/abstract_S0140525X99452197
  
• Evan Tiffany (1999). Semantics San Diego style.   (More)
  Additional links for this entry:
  http://links.jstor.org/sici?sici=0022-362X(199908)96:8<416:SSDS>2.0.CO;2-N
  http://www.jstor.org/sici?sici=0022-362X(199908)96:8<416:SSDS>2.0.CO;2-N
  http://www.jstor.org/stable/pdfplus/2564630.pdf
  
• Tim van Gelder (1999). Distributed vs. local representation.   (Abstract & more)
  Abstract: been to define various notions of distribution in terms of represented by one and the same distributed pattern (Mur- structures of correspondence between the represented items dock 1979). For example, it is standard in feedforward and the representational resources (e.g., van Gelder 1992). connectionist networks for one and the same set of synap- This approach may be misguided; the essence of this alter- tic weights to represent many associations between input native category of representation might be some other prop- and output. erty entirely. For example, Haugeland (1991) has suggested • Equipotentiality In some cases, an item is represented by
  Additional links for this entry:
  http://www.arts.unimelb.edu.au/~tgelder/papers/MITDist.pdf
  http://www.philosophy.unimelb.edu.au/tgelder/papers/MITDist.pdf
  http://www.phil.canterbury.ac.nz/tom_bestor/e-texts/MITECS - Distributed vs Local Representation - van Gelder.pdf
  
• Tim van Gelder (1990). Why distributed representation is inherently non-symbolic.   (Abstract & more)
  Abstract: There are many conflicting views concerning the nature of distributed representation, its compatibility or otherwise with symbolic representation, and its importance in characterizing the nature of connectionist models and their relationship to more traditional symbolic approaches to understanding cognition. Many have simply assumed that distribution is merely an implementation issue, and that symbolic mechanisms can be designed to take advantage of the virtues of distribution if so desired. Others, meanwhile, see the use of distributed representation as marking a fundamental difference between the two approaches. One reason for this diversity of opinion is the fact that the relevant notions - especially that of
  Additional links for this entry:
  http://www.arts.unimelb.edu.au/~tgelder/papers/DRNS.html
  http://www.philosophy.unimelb.edu.au/tgelder/papers/DRNS.html
  
• Jonathan Waskan (2001). A critique of connectionist semantics.   (More)
  Additional links for this entry:
  http://www.ingentaconnect.com/content/tandf/ccos/2001/00000013/00000003/art00004
  http://taylorandfrancis.metapress.com/index/WGXAHC9FUKFKEVME.pdf
  http://www.informaworld.com/index/WGXAHC9FUKFKEVME.pdf
  

20 displayed