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6.3b. Representation in Connectionism (Representation in Connectionism on PhilPapers)

See also:
Bechtel, William P. (1994). Natural deduction in connectionist systems. Synthese 101 (3):433-463.   (Cited by 7 | Google | More links)
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
Butler, Keith (1995). Representation and computation in a deflationary assessment of connectionist cognitive science. Synthese 104 (1):71-97.   (Google | More links)
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
Calvo Garzón, Francisco (2000). A connectionist defence of the inscrutability thesis. Mind and Language 15 (5):465-480.   (Google)
Calvo Garzón, Francisco (2003). Connectionist semantics and the collateral information challenge. Mind and Language 18 (1):77-94.   (Google)
Calvo Garzón, Francisco (2000). State space semantics and conceptual similarity: Reply to Churchland. Philosophical Psychology 13 (1):77-95.   (Google)
Abstract: Jerry Fodor and Ernest Lepore [(1992) Holism: a shopper's guide, Oxford: Blackwell; (1996) in R. McCauley (Ed.) The Churchlands and their critics , Cambridge: Blackwell] have launched a powerful attack against Paul Churchland's connectionist theory of semantics--also known as state space semantics. In one part of their attack, Fodor and Lepore argue that the architectural and functional idiosyncrasies of connectionist networks preclude us from articulating a notion of conceptual similarity applicable to state space semantics. Aarre Laakso and Gary Cottrell [(1998) in M. A. Gernsbacher & S. Derry (Eds) Proceedings of the 20th Annual Conference of the Cognitive Science Society, Mahway, NJ: Erlbaum; Philosophical Psychology ] 13, 47-76 have recently run a number of simulations on simple feedforward networks and applied a mathematical technique for measuring conceptual similarity in the representational spaces of those networks. Laakso and Cottrell contend that their results decisively refute Fodor and Lepore's criticisms. Paul Churchland [(1998) Journal of Philosophy, 95, 5-32 ] goes further. He uses Laakso and Cottrell's neurosimulations to argue that connectionism does furnish us with all we need to construct a robust theory of semantics and a robust theory of translation. In this paper I shall argue that whereas Laakso and Cottrell's neurocomputational results may provide us with a rebuttal of Fodor and Lepore's argument, Churchland's conclusion is far too optimistic. In particular, I shall try to show that connectionist modelling does not provide any objective criterion for achieving a one-to-one accurate translational mapping across networks
Cilliers, F. P. (1991). Rules and relations: Some connectionist implications for cognitive science and language. South African Journal of Philosophy 49 (May):49-55.   (Cited by 1 | Google)
Clark, Andy (1993). Associative Engines: Connectionism, Concepts, and Representational Change. MIT Press.   (Cited by 222 | Google | More links)
Abstract: As Ruben notes, the macrostrategy can allow that the distinction may also be drawn at some micro level, but it insists that descent to the micro level is ...
Clark, Andy (ms). Connectionism, nonconceptual content, and representational redescription.   (Annotation | Google)
Clark, Andy & Karmiloff-Smith, Annette (1994). The cognizer's innards: A psychological and philosophical perspective on the development of thought. Mind and Language 8 (4):487-519.   (Cited by 196 | Annotation | Google | More links)
Cummins, Robert E. (1991). The role of representation in connectionist explanation of cognitive capacities. In William Ramsey, Stephen P. Stich & D. Rumelhart (eds.), Philosophy and Connectionist Theory. Lawrence Erlbaum.   (Cited by 8 | Annotation | Google)
Cussins, Adrian (1990). The connectionist construction of concepts. In Margaret A. Boden (ed.), The Philosophy of AI. Oxford University Press.   (Cited by 107 | Annotation | Google)
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)
Eliasmith, Chris (online). Structure without symbols: Providing a distributed account of high-level cognition.   (Google)
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
Garzon, Francisco Calvo (2000). A connectionist defence of the inscrutability thesis. Mind and Language 15 (5):465-480.   (Cited by 4 | Google | More links)
Garzon, Francisco Calvo (2000). State space semantics and conceptual similarity: Reply to Churchland. Philosophical Psychology 13 (1):77-96.   (Cited by 8 | Google | More links)
Abstract: Jerry Fodor and Ernest Lepore [(1992) Holism: a shopper's guide, Oxford: Blackwell; (1996) in R. McCauley (Ed.) The Churchlands and their critics , Cambridge: Blackwell] have launched a powerful attack against Paul Churchland's connectionist theory of semantics--also known as state space semantics. In one part of their attack, Fodor and Lepore argue that the architectural and functional idiosyncrasies of connectionist networks preclude us from articulating a notion of conceptual similarity applicable to state space semantics. Aarre Laakso and Gary Cottrell [(1998) in M. A. Gernsbacher & S. Derry (Eds) Proceedings of the 20th Annual Conference of the Cognitive Science Society, Mahway, NJ: Erlbaum; Philosophical Psychology ] 13, 47-76 have recently run a number of simulations on simple feedforward networks and applied a mathematical technique for measuring conceptual similarity in the representational spaces of those networks. Laakso and Cottrell contend that their results decisively refute Fodor and Lepore's criticisms. Paul Churchland [(1998) Journal of Philosophy, 95, 5-32 ] goes further. He uses Laakso and Cottrell's neurosimulations to argue that connectionism does furnish us with all we need to construct a robust theory of semantics and a robust theory of translation. In this paper I shall argue that whereas Laakso and Cottrell's neurocomputational results may provide us with a rebuttal of Fodor and Lepore's argument, Churchland's conclusion is far too optimistic. In particular, I shall try to show that connectionist modelling does not provide any objective criterion for achieving a one-to-one accurate translational mapping across networks
Gauker, Christopher (2007). A critique of the similarity space theory of concepts. Mind and Language 22 (4):317–345.   (Google | More links)
Abstract: A similarity space is a hyperspace in which the dimensions represent various dimensions on which objects may differ. The similarity space theory of concepts is the thesis that concepts are regions of similarity spaces that are somehow realized in the brain. Proponents of such a theory of concepts include Paul Churchland and Peter Gärdenfors. This paper argues that the similarity space theory of concepts is mistaken because regions of similarity spaces cannot serve as the components of judgments. It emerges that although similarity spaces cannot model concepts, they may model a kind of nonconceptual representation
Goschke, T. & Koppelberg, Dirk (1990). Connectionism and the semantic content of internal representation. Review of International Philosophy 44 (172):87-103.   (Google)
Goschke, T. & Koppelberg, Dirk (1991). The concept of representation and the representation of concepts in connectionist models. In William Ramsey, Stephen P. Stich & D. Rumelhart (eds.), Philosophy and Connectionist Theory. Lawrence Erlbaum.   (Cited by 17 | Annotation | Google)
Hadley, Robert F. (2004). On the proper treatment of semantic systematicity. Minds and Machines 14 (2):145-172.   (Cited by 7 | Google | More links)
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
Haselager, W. F. G. (1999). On the potential of non-classical constituency. Acta Analytica 22 (22):23-42.   (Cited by 4 | Google | More links)
Hatfield, Gary (1991). Representation and rule-instantiation in connectionist systems. In Terence E. Horgan & John L. Tienson (eds.), Connectionism and the Philosophy of Mind. Kluwer.   (Cited by 11 | Annotation | Google)
Hatfield, Gary (1991). Representation in perception and cognition: Connectionist affordances. In William Ramsey, Stephen P. Stich & D. Rumelhart (eds.), Philosophy and Connectionist Theory. Lawrence Erlbaum.   (Cited by 49 | Google)
Haybron, Daniel M. (2000). The causal and explanatory role of information stored in connectionist networks. Minds and Machines 10 (3):361-380.   (Cited by 2 | Google | More links)
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
Laakso, Aarre & Cottrell, Garrison W. (2000). Content and cluster analysis: Assessing representational similarity in neural systems. Philosophical Psychology 13 (1):47-76.   (Cited by 18 | Google | More links)
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
Lormand, Eric (ms). Connectionist content.   (Google)
Mandik, Pete (2003). Varieties of representation in evolved and embodied neural networks. Biology and Philosophy 18 (1):95-130.   (Cited by 6 | Google | More links)
Abstract:   In this paper I discuss one of the key issuesin the philosophy of neuroscience:neurosemantics. The project of neurosemanticsinvolves explaining what it means for states ofneurons and neural systems to haverepresentational contents. Neurosemantics thusinvolves issues of common concern between thephilosophy of neuroscience and philosophy ofmind. I discuss a problem that arises foraccounts of representational content that Icall ``the economy problem'': the problem ofshowing that a candidate theory of mentalrepresentation can bear the work requiredwithin in the causal economy of a mind and anorganism. My approach in the current paper isto explore this and other key themes inneurosemantics through the use of computermodels of neural networks embodied and evolvedin virtual organisms. The models allow for thelaying bare of the causal economies of entireyet simple artificial organisms so that therelations between the neural bases of, forinstance, representation in perception andmemory can be regarded in the context of anentire organism. On the basis of thesesimulations, I argue for an account ofneurosemantics adequate for the solution of theeconomy problem
Markic, Olga (1995). Finding the right level for connectionist representations (a critical note on Ramsey's paper). Acta Analytica 14 (14):27-35.   (Google)
O'Brien, Gerard (1989). Connectionism, analogicity and mental content. Acta Analytica 22 (22):111-31.   (Google | More links)
Abstract: In Connectionism and the Philosophy of Psychology, Horgan and Tienson (1996) argue that cognitive processes, pace classicism, are not governed by exceptionless, “representation-level” rules; they are instead the work of defeasible cognitive tendencies subserved by the non-linear dynamics of the brain’s neural networks. Many theorists are sympathetic with the dynamical characterisation of connectionism and the general (re)conception of cognition that it affords. But in all the excitement surrounding the connectionist revolution in cognitive science, it has largely gone unnoticed that connectionism adds to the traditional focus on computational processes, a new focus – one on the vehicles of mental representation, on the entities that carry content through the mind. Indeed, if Horgan and Tienson’s dynamical characterisation of connectionism is on the right track, then so intimate is the relationship between computational processes and representational vehicles, that connectionist cognitive science is committed to a resemblance theory of mental content
O'Brien, Gerard & Opie, Jonathan (2004). Notes toward a structuralist theory of mental representation. In Hugh Clapin (ed.), Representation in Mind. Elsevier.   (Google)
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
Place, Ullin T. (1989). Toward a connectionist version of the causal theory of reference. Acta Analytica 4 (5):71-97.   (Google)
Potrc, Matjaz (1999). Morphological content. Acta Analytica 22 (22):133-149.   (Google)
Prinz, Jesse J. (2006). Empiricism and state-space semantics. In Brian L Keeley (ed.), Paul Churchland. Cambridge: Cambridge University Press.   (Google)
Ramsey, William (1997). Do connectionist representations earn their explanatory keep? Mind and Language 12 (1):34-66.   (Cited by 16 | Annotation | Google | More links)
Ramsey, William (1995). Rethinking distributed representation. Acta Analytica 10 (14):9-25.   (Cited by 1 | Google)
Schopman, Joop & Shawky, A. (1999). Remarks on the impact of connectionism on our thinking about concepts. In Peter Millican & A. Clark (eds.), Connectionism, Concepts and Folk Psychology. Oxford University Press.   (Google)
Shea, Nicholas (2007). Content and its vehicles in connectionist systems. Mind and Language 22 (3):246–269.   (Google | More links)
Abstract: This paper advocates explicitness about the type of entity to be considered as content- bearing in connectionist systems; it makes a positive proposal about how vehicles of content should be individuated; and it deploys that proposal to argue in favour of representation in connectionist systems. The proposal is that the vehicles of content in some connectionist systems are clusters in the state space of a hidden layer. Attributing content to such vehicles is required to vindicate the standard explanation for some classificatory networks’ ability to generalise to novel samples their correct classification of the samples on which they were trained
Stone, Tony & Davies, Martin (2000). Autonomous psychology and the moderate neuron doctrine. Behavioral and Brain Sciences 22 (5):849-850.   (Cited by 4 | Google | More links)
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._
Tiffany, Evan (1999). Semantics San Diego style. Journal of Philosophy 96 (8):416-429.   (Cited by 6 | Google | More links)
Tye, Michael (1987). Representation in pictorialism and connectionism. Southern Journal of Philosophy Supplement 26:163-184.   (Annotation | Google)
van Gelder, Tim (1999). Distributed vs. local representation. In R.A. Wilson & F.C. Keil (eds.), The MIT Encyclopedia of the Cognitive Sciences. MIT Press.   (Cited by 6 | Google)
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
van Gelder, Tim (1990). Why distributed representation is inherently non-symbolic. In G. Dorffner (ed.), Konnektionismus in Artificial Intelligence Und Kognitionsforschung. Berlin: Springer-Verlag.   (Cited by 4 | Google)
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
van Gelder, Tim (1991). What is the D in PDP? In William Ramsey, Stephen P. Stich & D. Rumelhart (eds.), Philosophy and Connectionist Theory. Lawrence Erlbaum.   (Cited by 65 | Annotation | Google)
Von Eckardt, Barbara (2003). The explanatory need for mental representations in cognitive science. Mind and Language 18 (4):427-439.   (Cited by 1 | Google | More links)
Abstract:   Ramsey (1997) argues that connectionist representations 'do not earn their explanatory keep'. The aim of this paper is to examine the argument Ramsey gives to support that conclusion. In doing so, I identify two kinds of explanatory need—need relative to a possible explanation and need relative to a true explanation and argue that internal representations are not needed for either connectionist or nonconnectionist possible explanations but that it is quite likely that they are needed for true explanations. However, to show that the latter is the case requires more than a consideration of the form of explanation involved
Waskan, Jonathan A. (2001). A critique of connectionist semantics. Connection Science 13 (3):277-292.   (Google | More links)