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  1. added 2019-06-06
    Connectionism and the Philosophical Foundations of Cognitive Science.Terence E. Horgan - 1997 - Metaphilosophy 28 (1-2):1-30.
    This is an overview of recent philosophical discussion about connectionism and the foundations of cognitive science. Connectionist modeling in cognitive science is described. Three broad conceptions of the mind are characterized, and their comparative strengths and weaknesses are discussed: the classical computation conception in cognitive science; a popular foundational interpretation of connectionism that John Tienson and I call “non‐sentential computationalism”; and an alternative interpretation of connectionism we call “dynamical cognition.” Also discussed are two recent philosophical attempts to enlist connectionism in (...)
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  2. added 2018-02-17
    Connectionism: Theorye and Practice.Steven Davis (ed.) - 1991 - Oxford University Press.
  3. added 2016-12-08
    Philosophical Issues in Brain Theory and Connectionism.Chris Eliasmith & Andy Clark - 2002 - 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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  4. added 2016-12-08
    Can Connectionist Models Exhibit Non-Classical Structure Sensitivity?Tim van Gelder - manuscript
    Department of Computer Science Philosophy Program, Research School of Social Sciences University of Skövde, S-54128, SWEDEN Australian National University, Canberra ACT 0200.
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  5. added 2016-11-03
    Advice Seeking Network Structures and the Learning Organization.Jarle Aarstad, Marcus Selart & Sigurd Troye - 2011 - Problems and Perspectives in Management 9 (2):44-51.
    Organizational learning can be described as a transfer of individuals’ cognitive mental models to shared mental models. Employees, seeking the same colleagues for advice, are structurally equivalent, and the aim of the paper is to study if the concept can act as a conduit for organizational learning. It is argued that the mimicking of colleagues’ advice seeking structures will induce structural equivalence and transfer the accuracy of individuals’ cognitive mental models to shared mental models. Taking a dyadic level of analysis (...)
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  6. added 2015-09-10
    Another Look at McCulloch and Pitts's “Logical Calculus”.Ken Aizawa - manuscript
    To date, almost every historical examination of Warren McCulloch and Walter Pitts’s, “A Logical Calculus of the Ideas Immanent in Nervous Activity” has focused its attention on one dimension of their paper, namely, the attempt to relate neuronal action potentials to formulae in (an extension of) Boolean logic.[1] The implicit justification for this focus begins with the observation that this constitutes the most substantial conceptual innovation of the paper. Earlier work in theoretical neurophysiology had provided mathematical descriptions of neural networks (...)
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  7. added 2014-08-02
    The Language of Thought Hypothesis.Murat Aydede - 2010 - Stanford Encyclopedia of Philosophy.
    A comprehensive introduction to the Language of Though Hypothesis (LOTH) accessible to general audiences. LOTH is an empirical thesis about thought and thinking. For their explication, it postulates a physically realized system of representations that have a combinatorial syntax (and semantics) such that operations on representations are causally sensitive only to the syntactic properties of representations. According to LOTH, thought is, roughly, the tokening of a representation that has a syntactic (constituent) structure with an appropriate semantics. Thinking thus consists in (...)
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  8. added 2014-04-23
    The Newell Test for a Theory of Cognition.John R. Anderson & Christian Lebiere - 2003 - Behavioral and Brain Sciences 26 (5):587-601.
    Newell proposed that cognitive theories be developed in an effort to satisfy multiple criteria and to avoid theoretical myopia. He provided two overlapping lists of 13 criteria that the human cognitive architecture would have to satisfy in order to be functional. We have distilled these into 12 criteria: flexible behavior, real-time performance, adaptive behavior, vast knowledge base, dynamic behavior, knowledge integration, natural language, learning, development, evolution, and brain realization. There would be greater theoretical progress if we evaluated theories by a (...)
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  9. added 2014-04-23
    Locality, Modularity, and Computational Neural Networks.Horst Bischof - 1997 - Behavioral and Brain Sciences 20 (3):516-517.
    There is a distinction between locality and modularity. These two terms have often been used interchangeably in the target article and commentary. Using this distinction we argue in favor of a modularity. In addition we also argue that both PDP-type networks and box-and-arrow models have their own strengths and pitfalls.
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  10. added 2014-04-03
    Derrida and Connectionism: Differance in Neural Nets.Gordon G. Globus - 1992 - Philosophical Psychology 5 (2):183-97.
    A possible relation between Derrida's deconstruction of metaphysics and connectionism is explored by considering diffeacuterance in neural nets terms. First diffeacuterance, as the crossing of Saussurian difference and Freudian deferral, is modeled and then the fuller 'sheaf of diffeacuterance is taken up. The metaphysically conceived brain has two versions: in the traditional computational version the brain processes information like a computer and in the connectionist version the brain computes input vector to output vector transformations non-symbolically. The 'deconstructed brain' neither processes (...)
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  11. added 2014-04-03
    Are Connectionist Models Cognitive?Benny Shanon - 1992 - Philosophical Psychology 5 (3):235-255.
    In their critique of connectionist models Fodor and Pylyshyn (1988) dismiss such models as not being cognitive or psychological. Evaluating Fodor and Pylyshyn's critique requires examining what is required in characterizating models as 'cognitive'. The present discussion examines the various senses of this term. It argues the answer to the title question seems to vary with these different senses. Indeed, by one sense of the term, neither representa-tionalism nor connectionism is cognitive. General ramifications of such an appraisal are discussed and (...)
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  12. added 2014-04-03
    Connectionism, Modularity, and Tacit Knowledge.Martin Davies - 1989 - British Journal for the Philosophy of Science 40 (December):541-55.
    In this paper, I define tacit knowledge as a kind of causal-explanatory structure, mirroring the derivational structure in the theory that is tacitly known. On this definition, tacit knowledge does not have to be explicitly represented. I then take the notion of a modular theory, and project the idea of modularity to several different levels of description: in particular, to the processing level and the neurophysiological level. The fundamental description of a connectionist network lies at a level between the processing (...)
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  13. added 2014-04-02
    Connectionism and the Rationale Constraint on Cognitive Explanations.Robert Cummins - 1995 - Philosophical Perspectives 9:105-25.
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  14. added 2014-04-02
    The Path Beyond First-Order Connectionism.William P. Bechtel - 1993 - Mind and Language 8 (4):531-539.
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  15. added 2014-04-02
    Cognizers' Innards and Connectionist Nets: A Holy Alliance?Adele Abrahamsen - 1993 - Mind and Language 8 (4):520-530.
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  16. added 2014-04-02
    Connectionism, Competence and Explanation.Andy Clark - 1990 - British Journal for the Philosophy of Science 41 (June):195-222.
    A competence model describes the abstract structure of a solution to some problem. or class of problems, facing the would-be intelligent system. Competence models can be quite derailed, specifying far more than merely the function to be computed. But for all that, they are pitched at some level of abstraction from the details of any particular algorithm or processing strategy which may be said to realize the competence. Indeed, it is the point and virtue of such models to specify some (...)
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  17. added 2014-04-01
    Wittgenstein and Connectionism: A Significant Complementarity?Stephen L. Mills - 1993 - Philosophy 34:137-157.
    Between the later views of Wittgenstein and those of connectionism 1 on the subject of the mastery of language there is an impressively large number of similarities. The task of establishing this claim is carried out in the second section of this paper.
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  18. added 2014-03-31
    The Philosophical Import of Connectionism: A Critical Notice of Andy Clark's Associative Engines.Manuel García-Carpintero - 1995 - Mind and Language 10 (4):370-401.
    Critical notice of Andy Clark's "Associative Engines".
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  19. added 2014-03-30
    Comments on Bechtel's The Case for Connectionism.Drew Christie - 1993 - Philosophical Studies 71 (2):155-162.
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  20. added 2014-03-30
    The Case for Connectionism.William Bechtel - 1993 - Philosophical Studies 71 (2):119-54.
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  21. added 2014-03-28
    Connectionism and Novel Combinations of Skills: Implications for Cognitive Architecture. [REVIEW]Robert F. Hadley - 1999 - Minds and Machines 9 (2):197-221.
    In the late 1980s, there were many who heralded the emergence of connectionism as a new paradigm – one which would eventually displace the classically symbolic methods then dominant in AI and Cognitive Science. At present, there remain influential connectionists who continue to defend connectionism as a more realistic paradigm for modeling cognition, at all levels of abstraction, than the classical methods of AI. Not infrequently, one encounters arguments along these lines: given what we know about neurophysiology, it is just (...)
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  22. added 2014-03-26
    Connectionism and the Causal Theory of Action Explanation.Scott R. Sehon - 1998 - Philosophical Psychology 11 (4):511-532.
    It is widely assumed that common sense psychological explanations of human action are a species of causal explanation. I argue against this construal, drawing on Ramsey et al.'s paper, “Connectionism, eliminativism, and the future of folk psychology”. I argue that if certain connec-tionist models are correct, then mental states cannot be identified with functionally discrete causes of behavior, and I respond to some recent attempts to deny this claim. However, I further contend that our common sense psychological practices are not (...)
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  23. added 2014-03-22
    Connectionism Today.Kim Plunkett - 2001 - Synthese 129 (2):185-194.
    Connectionist networks have been used to model a wide range of cognitivephenomena, including developmental, neuropsychological and normal adultbehaviours. They have offered radical alternatives to traditional accounts ofwell-established facts about cognition. The primary source of the success ofthese models is their sensitivity to statistical regularities in their trainingenvironment. This paper provides a brief description of the connectionisttoolbox and how this has developed over the past 2 decades, with particularreference to the problem of reading aloud.
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  24. added 2014-03-22
    Filling the Gaps: Hume and Connectionism on the Continued Existence of Unperceived Objects.Mark Collier - 1999 - Hume Studies 25 (1 and 2):155-170.
    In Book I, part iv, section 2 of the Treatise, "Of scepticism with regard to the senses," Hume presents two different answers to the question of how we come to believe in the continued existence of unperceived objects. He rejects his first answer shortly after its formulation, and the remainder of the section articulates an alternative account of the development of the belief. The account that Hume adopts, however, is susceptible to a number of insurmountable objections, which motivates a reassessment (...)
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  25. added 2014-03-17
    Churchland on Connectionism.Aarre Laakso & Garrison W. Cottrell - 2006 - In Brian L. Keeley (ed.), Paul Churchland. Cambridge: Cambridge University Press.
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  26. added 2014-03-09
    Connectionism: Debates on Psychological Explanation.Cynthia Macdonald & Graham Macdonald (eds.) - 1995 - Blackwell.
    This volume provides an introduction to and review of key contemporary debates concerning connectionism, and the nature of explanation and methodology in cognitive psychology. The first debate centers on the question of whether human cognition is best modeled by classical or by connectionist architectures. The second centres on the question of the compatibility between folk, or commonsense, psychological explanation and explanations based on connectionist models of cognition. Each of the two sections includes a classic reading along with important responses, and (...)
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  27. added 2014-02-20
    Connectionist Hysteria: Reducing a Freudian Case Study to a Network Model.Dan Lloyd - 1994 - Philosophy, Psychiatry, and Psychology 1 (2):69-88.
    Connectionism—also known as parallel distributed processing, or neural network modeling—offers promise as a framework to unite clinical and cognitive psychology, and as a tool for studying conscious and unconscious mental activity. This paper describes a neural network model of the case study of Lucy R., from Freud and Breuer's Studies on Hysteria. Though very simple in architecture, the network spontaneously displays analogues of repression and hallucination, corresponding to Lucy R.'s symptoms. Salient elements of Lucy's conscious experience are represented in the (...)
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  28. added 2014-02-18
    Logic in Cognitive Science: Bridging the Gap Between Symbolic and Connectionist Paradigms.Alistair Isaac & Jakub Szymanik - 2010 - Journal of the Indian Council of Philosophical Research (2):279-309.
    This paper surveys applications of logical methods in the cognitive sciences. Special attention is paid to non-monotonic logics and complexity theory. We argue that these particular tools have been useful in clarifying the debate between symbolic and connectionist models of cognition.
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  29. added 2014-01-21
    Reduction and Levels of Explanation in Connectionism.John Sutton - 1995 - In P. Slezak, T. Caelli & R. Clark (eds.), Perspectives on cognitive science: theories, experiments, and foundations. Ablex. pp. 347-368.
    Recent work in the methodology of connectionist explanation has I'ocrrsccl on the notion of levels of explanation. Specific issucs in conncctionisrn hcrc intersect with rvider areas of debate in the philosophy of psychology and thc philosophy of science generally. The issues I raise in this chapter, then, are not unique to cognitive science; but they arise in new and important contexts when connectionism is taken seriously as a model of cognition. The general questions are the relation between levels and the (...)
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  30. added 2011-10-30
    How Do Connectionist Networks Compute?Gerard O'Brien & Jonathan Opie - 2006 - Cognitive Processing 7 (1):30-41.
    Although connectionism is advocated by its proponents as an alternative to the classical computational theory of mind, doubts persist about its _computational_ credentials. Our aim is to dispel these doubts by explaining how connectionist networks compute. We first develop a generic account of computation—no easy task, because computation, like almost every other foundational concept in cognitive science, has resisted canonical definition. We opt for a characterisation that does justice to the explanatory role of computation in cognitive science. Next we examine (...)
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  31. added 2011-10-30
    Connectionist Modelling Strategies.Jonathan Opie - 1998 - Psycoloquy 9 (30).
    Green offers us two options: either connectionist models are literal models of brain activity or they are mere instruments, with little or no ontological significance. According to Green, only the first option renders connectionist models genuinely explanatory. I think there is a third possibility. Connectionist models are not literal models of brain activity, but neither are they mere instruments. They are abstract, IDEALISED models of the brain that are capable of providing genuine explanations of cognitive phenomena.
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  32. added 2011-07-05
    On Qualitative Modelling.Jarmo J. Ahonen - 1994 - AI and Society 8 (1):17-28.
    Fundamental assumptions behind qualitative modelling are critically considered and some inherent problems in that modelling approach are outlined. The problems outlined are due to the assumption that a sufficient set of symbols representing the fundamental features of the physical world exists. That assumption causes serious problems when modelling continuous systems. An alternative for intelligent system building for cases not suitable for qualitative modelling is proposed. The proposed alternative combines neural networks and quantitative modelling.
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  33. added 2010-06-22
    Proceedings of the 2007 International Joint Conference on Neural Networks.Gualtiero Piccinini (ed.) - 2007
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  34. added 2010-06-22
    Paul Churchland.Brian L. Keeley (ed.) - 2005 - Cambridge: Cambridge University Press.
  35. added 2010-06-22
    The Handbook of Brain Theory and Neural Networks, Second Edition.Michael A. Arbib (ed.) - 2002 - MIT Press.
    A new, dramatically updated edition of the classic resource on the constantly evolving fields of brain theory and neural networks.
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  36. added 2010-06-22
    Hayek: Economist and Social Philosopher: A Critical Retrospect.Stephen F. Frowen (ed.) - 1997 - St. Martin's Press.
  37. added 2010-06-22
    The Churchlands and Their Critics.William P. Bechtel - 1996 - Oxford University Press.
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  38. added 2010-06-22
    Connectionism: Debates on Psychological Explanation.Andy Clark - 1995 - Cambridge: Blackwell.
  39. added 2010-06-22
    Phenomenology of the Cultural Disciplines.Thomas J. Nenon - 1994 - Dordrecht: Kluwer Academic Publishers.
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  40. added 2010-06-22
    Minds: Natural and Artificial.Robert G. Burton (ed.) - 1992 - SUNY Press.
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  41. added 2010-06-22
    The Representational Theory of Mind.Kim Sterelny - 1990 - Blackwell.
  42. added 2010-06-22
    Neural Connections, Mental Computations.L. Nadel (ed.) - 1989 - MIT Press.
  43. added 2010-06-22
    Simple Minds.Dan Lloyd - 1989 - MIT Press.
    Drawing on philosophy, neuroscience, and artificial intelligence, Simple Minds explores the construction of the mind from the matter of the brain.
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  44. added 2009-12-04
    PDP Learnability and Innate Knowledge of Language.David Kirsh - 1992 - In S. Davis (ed.), Connectionism: Theorye and Practice. Oxford University press.
    It is sometimes argued that if PDP networks can be trained to make correct judgements of grammaticality we have an existence proof that there is enough information in the stimulus to permit learning grammar by inductive means alone. This seems inconsistent superficially with Gold's theorem and at a deeper level with the fact that networks are designed on the basis of assumptions about the domain of the function to be learned. To clarify the issue I consider what we should learn (...)
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  45. added 2009-04-06
    Connectionism, Reduction, and Multiple Realizability.John Bickle - 1995 - Behavior and Philosophy 23 (2):29-39.
    I sketch a theory of cognitive representation from recent "connectionist" cognitive science. I then argue that (i) this theory is reducible to neuroscientific theories, yet (ii) its kinds are multiply realized at a neurobiological level. This argument demonstrates that multiple realizability alone is no barrier to the reducibility of psychological theories. I conclude that the multiple realizability argument, the most influential argument against psychophysical reductionism, should be abandoned.
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  46. added 2008-12-31
    Some Myths of Connectionism.István S. N. Berkeley - manuscript
    Since the emergence of what Fodor and Pylyshyn (1988) call 'new connectionism', there can be little doubt that connectionist research has become a significant topic for discussion in the Philosophy of Cognitive Science and the Philosophy of Mind. In addition to the numerous papers on the topic in philosophical journals, almost every recent book in these areas contain at least a brief reference to, or discussion of, the issues raised by connectionist research (see Sterelny 1990, Searle, 1992, and O Nualláin, (...)
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  47. added 2008-12-31
    What is Connectionism?Istvan S. N. Berkeley - manuscript
    Connectionism is a style of modeling based upon networks of interconnected simple processing devices. This style of modeling goes by a number of other names too. Connectionist models are also sometimes referred to as 'Parallel Distributed Processing' (or PDP for short) models or networks.1 Connectionist systems are also sometimes referred to as 'neural networks' (abbreviated to NNs) or 'artificial neural networks' (abbreviated to ANNs). Although there may be some rhetorical appeal to this neural nomenclature, it is in fact misleading as (...)
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  48. added 2008-12-31
    Connectionist Computation.Gualtiero Piccinini - 2007 - In Proceedings of the 2007 International Joint Conference on Neural Networks.
    The following three theses are inconsistent: (1) (Paradigmatic) connectionist systems perform computations. (2) Performing computations requires executing programs. (3) Connectionist systems do not execute programs. Many authors embrace (2). This leads them to a dilemma: either connectionist systems execute programs or they don't compute. Accordingly, some authors attempt to deny (1), while others attempt to deny (3). But as I will argue, there are compelling reasons to accept both (1) and (3). So, we should replace (2) with a more satisfactory (...)
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  49. added 2008-12-31
    The Case of the Mysterious Mind: Review of Radiant Cool, by Dan Lloyd. [REVIEW]Susan J. Blackmore - 2003 - New Scientist 13:36-39.
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  50. added 2008-12-31
    Radical Connectionism: Thinking with (Not in) Language.Gerard O'Brien & Jonathan Opie - 2002 - Language and Communication 22 (3):313-329.
    In this paper we defend a position we call radical connectionism. Radical connectionism claims that cognition _never_ implicates an internal symbolic medium, not even when natural language plays a part in our thought processes. On the face of it, such a position renders the human capacity for abstract thought quite mysterious. However, we argue that connectionism is committed to an analog conception of neural computation, and that representation of the abstract is no more problematic for a system of analog vehicles (...)
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