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The Connectionist/Classical Debate

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  1. Frederick R. Adams, Kenneth Aizawa & Gary Fuller (1992). Rules in Programming Languages and Networks. In J. Dinsmore (ed.), The Symbolic and Connectionist Paradigms: Closing the Gap. Lawrence Erlbaum.
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  2. Kenneth Aizawa (1994). Representations Without Rules, Connectionism, and the Syntactic Argument. Synthese 101 (3):465-92.
    Terry Horgan and John Tienson have suggested that connectionism might provide a framework within which to articulate a theory of cognition according to which there are mental representations without rules (RWR) (Horgan and Tienson 1988, 1989, 1991, 1992). In essence, RWR states that cognition involves representations in a language of thought, but that these representations are not manipulated by the sort of rules that have traditionally been posited. In the development of RWR, Horgan and Tienson attempt to forestall a particular (...)
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  3. M. Arbib (2002). The Handbook of Brain Theory and Neural Networks. MIT Press.
    In hundreds of articles by experts from around the world, and in overviews and " road maps" prepared by the editor, "The Handbook of Brain Theory and Neural ...
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  4. Murat Aydede (1995). Connectionism and the Language of Thought. CSLI Technical Report.
    Fodor and Pylyshyn's (F&P) critique of connectionism has posed a challenge to connectionists: Adequately explain such nomological regularities as systematicity and productivity without postulating a "language of thought'' (LOT). Some connectionists declined to meet the challenge on the basis that the alleged regularities are somehow spurious. Some, like Smolensky, however, took the challenge very seriously, and attempted to meet it by developing models that are supposed to be non-classical.
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  5. Peter beim Graben (2004). Incompatible Implementations of Physical Symbol Systems. Mind and Matter 2 (2):29-51.
    Classical cognitive science assumes that intelligently behaving systems must be symbol processors that are implemented in physical systems such as brains or digital computers. By contrast, connectionists suppose that symbol manipulating systems could be approximations of neural networks dynamics. Both classicists and connectionists argue that symbolic computation and subsymbolic dynamics are incompatible, though on different grounds. While classicists say that connectionist architectures and symbol processors are either incompatible or the former are mere implementations of the latter, connectionists reply that neural (...)
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  6. Selmer Bringsjord (1991). Is the Connectionist-Logicist Debate One of Ai's Wonderful Red Herrings? Journal of Theoretical and Experimental Artificial Intelligence 3:319-49.
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  7. B. Chandrasekaran, A. Goel & D. Allemang (1988). Connectionism and Information-Processing Abstractions. AI Magazine 24.
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  8. Wayne D. Christensen & Luca Tomassi (2006). Neuroscience in Context: The New Flagship of the Cognitive Sciences. Biological Theory 1 (1):78-83.
    © 2006 Konrad Lorenz Institute for Evolution and Cognition Research.
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  9. Michael R. W. Dawson, D. A. Medler & Istvan S. N. Berkeley (1997). PDP Networks Can Provide Models That Are Not Mere Implementations of Classical Theories. Philosophical Psychology 10 (1):25-40.
    There is widespread belief that connectionist networks are dramatically different from classical or symbolic models. However, connectionists rarely test this belief by interpreting the internal structure of their nets. A new approach to interpreting networks was recently introduced by Berkeley et al. (1995). The current paper examines two implications of applying this method: (1) that the internal structure of a connectionist network can have a very classical appearance, and (2) that this interpretation can provide a cognitive theory that cannot be (...)
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  10. Daniel C. Dennett (1991). Mother Nature Versus the Walking Encyclopedia. In William Ramsey, Stephen P. Stich & D. Rumelhart (eds.), Philosophy and Connectionist Theory. Lawrence Erlbaum.
    In 1982, Feldman and Ballard published "Connectionist models and their properties" in Cognitive Science , helping to focus attention on a family of similarly inspired research strategies just then under way, by giving the family a name: "connectionism." Now, seven years later, the connectionist nation has swelled to include such subfamilies as "PDP" and "neural net models." Since the ideological foes of connectionism are keen to wipe it out in one fell swoop aimed at its "essence", it is worth noting (...)
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  11. Willem A. DeVries (1993). Who Sees with Equal Eye,... Atoms or Systems Into Ruin Hurl'd? Philosophical Studies 71 (2):191-200.
    A comment the paper by Brian McLaughlin in the same volume, this paper raises questions about whether the classicism/connectionism debate is really well-formed.
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  12. J. Dinsmore (1992). The Symbolic and Connectionist Paradigms: Closing the Gap. Lawrence Erlbaum.
    This book records the thoughts of researchers -- from both computer science and philosophy -- on resolving the debate between the symbolic and connectionist...
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  13. Michael G. Dyer (1991). Connectionism Versus Symbolism in High-Level Cognition. In Terence E. Horgan & John L. Tienson (eds.), Connectionism and the Philosophy of Mind. Kluwer.
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  14. Chris Eliasmith (2000). Is the Brain Analog or Digital? Cognitive Science Quarterly 1 (2):147-170.
    It will always remain a remarkable phenomenon in the history of philosophy, that there was a time, when even mathematicians, who at the same time were philosophers, began to doubt, not of the accuracy of their geometrical propositions so far as they concerned space, but of their objective validity and the applicability of this concept itself, and of all its corollaries, to nature. They showed much concern whether a line in nature might not consist of physical points, and consequently that (...)
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  15. Chris Eliasmith & Andy Clark (2002). Philosophical Issues in Brain Theory and Connectionism. In M. Arbib (ed.), The Handbook of Brain Theory and Neural Networks. Mit Press.
    In this article, we highlight three questions: (1) Does human cognition rely on structured internal representations? (2) How should theories, models and data relate? (3) In what ways might embodiment, action and dynamics matter for understanding the mind and the brain?
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  16. Jerry A. Fodor & Zenon W. Pylyshyn (1988). Connectionism and Cognitive Architecture. Cognition 28:3-71.
    This paper explores the difference between Connectionist proposals for cognitive a r c h i t e c t u r e a n d t h e s o r t s o f m o d e l s t hat have traditionally been assum e d i n c o g n i t i v e s c i e n c e . W e c l a i m t h a t t h (...)
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  17. James W. Garson (1994). No Representations Without Rules: The Prospects for a Compromise Between Paradigms in Cognitive Science. Mind and Language 9 (1):25-37.
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  18. James W. Garson (1994). Cognition Without Classical Architecture. Synthese 100 (2):291-306.
    Fodor and Pylyshyn (1988) argue that any successful model of cognition must use classical architecture; it must depend upon rule-based processing sensitive to constituent structure. This claim is central to their defense of classical AI against the recent enthusiasm for connectionism. Connectionist nets, they contend, may serve as theories of the implementation of cognition, but never as proper theories of psychology. Connectionist models are doomed to describing the brain at the wrong level, leaving the classical view to account for the (...)
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  19. Marcello Guarini (2001). A Defence of Connectionism Against the "Syntactic" Argument. Synthese 128 (3):287-317.
    In "Representations without Rules, Connectionism and the Syntactic Argument'', Kenneth Aizawa argues against the view that connectionist nets can be understood as processing representations without the use of representation-level rules, and he provides a positive characterization of how to interpret connectionist nets as following representation-level rules. He takes Terry Horgan and John Tienson to be the targets of his critique. The present paper marshals functional and methodological considerations, gleaned from the practice of cognitive modelling, to argue against Aizawa's characterization of (...)
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  20. Terence E. Horgan & John L. Tienson (2006). Cognition Needs Syntax but Not Rules. In Robert J. Stainton (ed.), Contemporary Debates in Cognitive Science. Malden MA: Blackwell Publishing.
    Human cognition is rich, varied, and complex. In this Chapter we argue that because of the richness of human cognition (and human mental life generally), there must be a syntax of cognitive states, but because of this very richness, cognitive processes cannot be describable by exceptionless rules. The argument for syntax, in Section 1, has to do with being able to get around in any number of possible environments in a complex world. Since nature did not know where in the (...)
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  21. Terence E. Horgan & John L. Tienson (1994). Representations Don't Need Rules: Reply to James Garson. Mind and Language 9 (1):1-24.
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  22. Terence E. Horgan & John L. Tienson (1989). Representation Without Rules. Philosophical Perspectives 17 (1):147-74.
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  23. Terence E. Horgan & John L. Tienson (1987). Settling Into a New Paradigm. Southern Journal of Philosophy Supplement 26 (S1):97-113.
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  24. Eric Lormand, Connectionist Languages of Thought.
    Fodor and Pylyshyn (1988) have presented an influential argument to the effect that any viable connectionist account of human cognition must implement a language of thought. Their basic strategy is to argue that connectionist models that do not implement a language of thought fail to account for the systematic relations among propositional attitudes. Several critics of the LOT hypothesis have tried to pinpoint flaws in Fodor and Pylyshyn’s argument (Smolensky 1989; Clark, 1989; Chalmers, 1990; Braddon-Mitchell and Fitzpatrick, 1990). One thing (...)
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  25. Eric Lormand (1991). Classical and Connectionist Models. Dissertation, Mit
    Much of the philosophical interest of cognitive science stems from its potential relevance to the mind/body problem. The mind/body problem concerns whether both mental and physical phenomena exist, and if so, whether they are distinct. In this chapter I want to portray the classical and connectionist frameworks in cognitive science as potential sources of evidence for or against a particular strategy for solving the mind/body problem. It is not my aim to offer a full assessment of these two frameworks in (...)
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  26. Brian P. McLaughlin & F. Warfield (1994). The Allure of Connectionism Reexamined. Synthese 101 (3):365-400.
    There is currently a debate over whether cognitive architecture is classical or connectionist in nature. One finds the following three comparisons between classical architecture and connectionist architecture made in the pro-connectionist literature in this debate: (1) connectionist architecture is neurally plausible and classical architecture is not; (2) connectionist architecture is far better suited to model pattern recognition capacities than is classical architecture; and (3) connectionist architecture is far better suited to model the acquisition of pattern recognition capacities by learning than (...)
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  27. William Ramsey, Stephen P. Stich & D. M. Rumelhart (1991). Philosophy and Connectionist Theory. Lawrence Erlbaum.
    The philosophy of cognitive science has recently become one of the most exciting and fastest growing domains of philosophical inquiry and analysis. Until the early 1980s, nearly all of the models developed treated cognitive processes -- like problem solving, language comprehension, memory, and higher visual processing -- as rule-governed symbol manipulation. However, this situation has changed dramatically over the last half dozen years. In that period there has been an enormous shift of attention toward connectionist models of cognition that are (...)
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  28. Susan Schneider (forthcoming). The Nature of Primitive Symbols in the Language of Thought. Mind and Language.
    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 (...)
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  29. Susan Schneider (2009). The Language of Thought. In John Symons & Paco Calvo (eds.), Routledge Companion to Philosophy of Psychology. Routledge.
    According to the language of thought (or.
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  30. Robert J. Stainton (2006). Contemporary Debates in Cognitive Science. Malden MA: Blackwell Publishing.