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Philosophy and Connectionist Theory

Hillsdale, N.J.: Lawrence Erlbaum (1991)

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  1. PDP networks can provide models that are not mere implementations of classical theories.Michael R. W. Dawson, David A. Medler & Istvan S. N. Berkeley - 1997 - 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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  • Connectionism and classical computation.Nick Chater - 1990 - Behavioral and Brain Sciences 13 (3):493-494.
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  • Representation and computation in a deflationary assessment of connectionist cognitive science.Keith Butler - 1995 - Synthese 104 (1):71-97.
    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 (...)
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  • Representational systems and symbolic systems.Gordon D. A. Brown & Mike Oaksford - 1990 - Behavioral and Brain Sciences 13 (3):492-493.
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  • What connectionists learn: Comparisons of model and neural nets.Bruce Bridgeman - 1990 - Behavioral and Brain Sciences 13 (3):491-492.
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  • Language learning in infancy: Does the empirical evidence support a domain specific language acquisition device?Christina Behme & Helene Deacon - 2008 - Philosophical Psychology 21 (5):641 – 671.
    Poverty of the Stimulus Arguments have convinced many linguists and philosophers of language that a domain specific language acquisition device (LAD) is necessary to account for language learning. Here we review empirical evidence that casts doubt on the necessity of this domain specific device. We suggest that more attention needs to be paid to the early stages of language acquisition. Many seemingly innate language-related abilities have to be learned over the course of several months. Further, the language input contains rich (...)
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  • Relatively local neurons in a distributed representation: A neurophysiological perspective.Shabtai Barash - 1990 - Behavioral and Brain Sciences 13 (3):489-491.
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  • What's Special About the Development of the Human Mind/Brain?Annette Karmiloff-Smith & Andy Clark - 1993 - Mind and Language 8 (4):569-581.
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  • Connectionist learning and the challenge of real environments.Mark Weaver & Stephen Kaplan - 1990 - Behavioral and Brain Sciences 13 (3):510-511.
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  • Connectionist models learn what?Timothy van Gelder - 1990 - Behavioral and Brain Sciences 13 (3):509-510.
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  • Advances in neural network theory.Gérard Toulouse - 1990 - Behavioral and Brain Sciences 13 (3):509-509.
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  • Connectionist models: Too little too soon?William Timberlake - 1990 - Behavioral and Brain Sciences 13 (3):508-509.
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  • Problems of extension, representation, and computational irreducibility.Patrick Suppes - 1990 - Behavioral and Brain Sciences 13 (3):507-508.
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  • The tripartite model of representation.Peter Slezak - 2002 - Philosophical Psychology 15 (3):239-270.
    Robert Cummins [(1996) Representations, targets and attitudes, Cambridge, MA: Bradford/MIT, p. 1] has characterized the vexed problem of mental representation as "the topic in the philosophy of mind for some time now." This remark is something of an understatement. The same topic was central to the famous controversy between Nicolas Malebranche and Antoine Arnauld in the 17th century and remained central to the entire philosophical tradition of "ideas" in the writings of Locke, Berkeley, Hume, Reid and Kant. However, the scholarly, (...)
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  • Structural content: A naturalistic approach to implicit belief.Paul Skokowski - 2004 - Philosophy of Science 71 (3):362-369.
    Various systems that learn are examined to show how content is carried in connections installed by a learning history. Agents do not explicitly use the content of such states in practical reasoning, yet the content plays an important role in explaining behavior, and the physical state carrying that content plays a role in causing behavior, given other occurrent beliefs and desires. This leads to an understanding of the environmental reasons which are the determinate content of these states, and leads to (...)
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  • Networks with Attitudes.Paul Skokowski - 2007 - Artificial Intelligence and Society 22 (3):461-470.
    Does connectionism spell doom for folk psychology? I examine the proposal that cognitive representational states such as beliefs can play no role if connectionist models - - interpreted as radical new cognitive theories -- take hold and replace other cognitive theories. Though I accept that connectionist theories are radical theories that shed light on cognition, I reject the conclusion that neural networks do not represent. Indeed, I argue that neural networks may actually give us a better working notion of cognitive (...)
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  • Networks with attitudes.Paul Skokowski - 2009 - AI and Society 23 (4):461-470.
    Does connectionism spell doom for folk psychology? I examine the proposal that cognitive representational states such as beliefs can play no role if connectionist models—interpreted as radical new cognitive theories—take hold and replace other cognitive theories. Though I accept that connectionist theories are radical theories that shed light on cognition, I reject the conclusion that neural networks do not represent. Indeed, I argue that neural networks may actually give us a better working notion of cognitive representational states such as beliefs, (...)
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  • RETRACTED ARTICLE: Contrasting Embodied Cognition with Standard Cognitive Science: A Perspective on Mental Representation.Pankaj Singh - 2019 - Journal of the Indian Council of Philosophical Research 36 (1):125-149.
    The proponents of embodied cognition often try to present their research program as the next step in the evolution of standard cognitive science. The domain of standard cognitive science is fairly clearly circumscribed (perception, memory, attention, language, problem solving, learning). Its ontological commitments, that is, its commitments to various theoretical entities, are overt: cognition involves algorithmic processes upon symbolic representations. As a research program, embodied cognition exhibits much greater latitude in subject matter, ontological commitment, and methodology than does standard cognitive (...)
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  • RETRACTED ARTICLE: Contrasting Embodied Cognition with Standard Cognitive Science: A Perspective on Mental Representation.Pankaj Singh - 2019 - Journal of the Indian Council of Philosophical Research 36 (1):125-149.
    The proponents of embodied cognition often try to present their research program as the next step in the evolution of standard cognitive science. The domain of standard cognitive science is fairly clearly circumscribed (perception, memory, attention, language, problem solving, learning). Its ontological commitments, that is, its commitments to various theoretical entities, are overt: cognition involves algorithmic processes upon symbolic representations. As a research program, embodied cognition exhibits much greater latitude in subject matter, ontological commitment, and methodology than does standard cognitive (...)
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  • There is more to learning then meeth the eye.Noel E. Sharkey - 1990 - Behavioral and Brain Sciences 13 (3):506-507.
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  • Psychoneural isomorphism: Historical background and current relevance.Eckart Scheerer - 1994 - Philosophical Psychology 7 (2):183-210.
    The relevance of Wolfgang K hler's psychoneural isomorphism principle to contemporary cognitive neuroscience is explored. K hler's approach to the mind—body problem is interpreted as a response to the foundational crisis of psychology at the beginning of the twentieth century. Some aspects of his isomorphism doctrine are discussed, with a view to reaching an interpretation that is both historically accurate and pertinent to issues currently debated in the philosophy of psychology. The principle was meant to be empirically verifiable. Accordingly, some (...)
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  • Arguing about representation.Mark Rowlands - 2017 - Synthese 194 (11):4215-4232.
    The question of whether cognition requires representations has engendered heated discussion during the last two decades. I shall argue that the question is, in all likelihood, a spurious one. There may or may not be a fact of the matter concerning whether a given item qualifies as a representation. However, even if there is, attempts to establish whether cognition requires representation have neither practical nor theoretical utility.
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  • Program execution in connectionist networks.Martin Roth - 2005 - Mind and Language 20 (4):448-467.
    Recently, connectionist models have been developed that seem to exhibit structuresensitive cognitive capacities without executing a program. This paper examines one such model and argues that it does execute a program. The argument proceeds by showing that what is essential to running a program is preserving the functional structure of the program. It has generally been assumed that this can only be done by systems possessing a certain temporalcausal organization. However, counterfactualpreserving functional architecture can be instantiated in other ways, for (...)
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  • Distributed representation and causal modularity: A rejoinder to Forster and Saidel.William Ramsey - 1994 - Philosophical Psychology 7 (4):453-61.
    In “Connectionism and the fats of folk psychology”, Forster and Saidel argue that the central claim of Ramsey, Stich and Garon (1991)—that distributed connectionist models are incompatible with the causal discreteness of folk psychology—is mistaken. To establish their claim, they offer an intriguing model which allegedly shows how distributed representations can function in a causally discrete manner. They also challenge our position regarding projectibility of folk psychology. In this essay, I offer a response to their account and show how their (...)
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  • Connectionism and three levels of nativism.William Ramsey & Stephen P. Stich - 1990 - Synthese 82 (2):177-205.
    Along with the increasing popularity of connectionist language models has come a number of provocative suggestions about the challenge these models present to Chomsky's arguments for nativism. The aim of this paper is to assess these claims. We begin by reconstructing Chomsky's argument from the poverty of the stimulus and arguing that it is best understood as three related arguments, with increasingly strong conclusions. Next, we provide a brief introduction to connectionism and give a quick survey of recent efforts to (...)
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  • The analysis of the learning needs to be deeper.John E. Rager - 1990 - Behavioral and Brain Sciences 13 (3):505-506.
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  • Realistic neural nets need to learn iconic representations.W. A. Phillips, P. J. B. Hancock & L. S. Smith - 1990 - Behavioral and Brain Sciences 13 (3):505-505.
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  • Learning from learned networks.M. Pavel - 1990 - Behavioral and Brain Sciences 13 (3):503-504.
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  • A Defense of Cartesian Materialism.Jonathan Opie - 1999 - Philosophy and Phenomenological Research 59 (4):939-963.
    One of the principal tasks Dennett sets himself in Consciousness Explained is to demolish the Cartesian theater model of phenomenal consciousness, which in its contemporary garb takes the form of Cartesian materialism: the idea that conscious experience is a process of presentation realized in the physical materials of the brain. The now standard response to Dennett is that, in focusing on Cartesian materialism, he attacks an impossibly naive account of consciousness held by no one currently working in cognitive science or (...)
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  • Cognitive science and phenomenal consciousness: A dilemma, and how to avoid it.Gerard O'Brien & Jon Opie - 1997 - Philosophical Psychology 10 (3):269-86.
    When it comes to applying computational theory to the problem of phenomenal consciousness, cognitive scientists appear to face a dilemma. The only strategy that seems to be available is one that explains consciousness in terms of special kinds of computational processes. But such theories, while they dominate the field, have counter-intuitive consequences; in particular, they force one to accept that phenomenal experience is composed of information processing effects. For cognitive scientists, therefore, it seems to come down to a choice between (...)
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  • Keeping representations at bay.Stanley Munsat - 1990 - Behavioral and Brain Sciences 13 (3):502-503.
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  • What about the unconscious?Chris Mortensen - 1999 - Behavioral and Brain Sciences 22 (1):162-162.
    O'Brien & Opie do not address the question of the psychotherapeutic role of unconscious representational states such as beliefs. A dilemma is proposed: if they accept the legitimacy of such states then they should modify what they say about dissociation, and if they do not, they owe us an account of why.
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  • Critical notices.Stephen Mills & Paul K. Moser - 1997 - International Journal of Philosophical Studies 5 (1):95 – 110.
    Connectionism: Debates on Psychological Explanation, Volume Two Edited by Cynthia Macdonald and Graham Macdonald Blackwell, 1995. Pp. xvii + 424. ISBN 0-631-19744-3. 50.00 (hbk). ISBN 0-631-19745-1 16.99 (pbk). New books on the philosophy of religion Divine Hiddenness and Human Reason By J.L. Schellenberg, Cornell University Press, 1993. Pp. 217. ISBN 0-8014-2792-4. $36.50 (hbk). Reason and the Heart By William J. Wainwright, Cornell University Press, 1995. Pp. 160. ISBN 0-8014-3139-5. $28.50 (hbk). The Rationality of Belief and the Plurality of Faith Edited (...)
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  • The connectionism/classicism battle to win souls.Brian P. McLaughlin - 1993 - Philosophical Studies 71 (2):163-190.
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  • Systematicity, Conceptual Truth, and Evolution.Brian P. McLaughlin - 1993 - Royal Institute of Philosophy Supplement 34:217-234.
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  • Systematicity, conceptual truth, and evolution.Brian P. McLaughlin - 1992 - Philosophy and the Cognitive Sciences 34:217-234.
    Smolensky's (1995) proposal for a connectionist explanation of systematicity doesn't work.
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  • What's new here?Bruce Mangan - 1999 - Behavioral and Brain Sciences 22 (1):160-161.
    O'Brien & Opie's (O&O's) theory demands a view of unconscious processing that is incompatible with virtually all current PDP models of neural activity. Relative to the alternatives, the theory is closer to an AI than a parallel distributed processing (PDP) perspective, and its treatment of phenomenology is ad hoc. It raises at least one important question: Could features of network relaxation be the “switch” that turns an unconscious into a conscious network?
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  • Toward a unification of conditioning and cognition in animal learning.William S. Maki - 1990 - Behavioral and Brain Sciences 13 (3):501-502.
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  • Replies to my critics. [REVIEW]Edouard Machery - 2010 - Philosophical Studies 149 (3):429 - 436.
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  • The neurocomputational mind meets normative epistemology.Kenneth R. Livingston - 1996 - Philosophical Psychology 9 (1):33-59.
    The rapid development of connectionist models in computer science and of powerful computational tools in neuroscience has encouraged eliminativist materialist philosophers to propose specific alternatives to traditional mentalistic theories of mind. One of the problems associated with such a move is that elimination of the mental would seem to remove access to ideas like truth as the foundations of normative epistemology. Thus, a successful elimination of propositional or sentential theories of mind must not only replace them for purposes of our (...)
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  • On learnability, empirical foundations, and naturalness.W. J. M. Levelt - 1990 - Behavioral and Brain Sciences 13 (3):501-501.
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  • Complexity and individual psychology.Yakir Levin & Itzhak Aharon - 2015 - Mind and Society 14 (2):203-219.
    In this paper we examine the question of whether complexity-like explanations can be applied to the psychology of individuals, and its implications for the scope of complexity explanations of social phenomena. We start by outlining two representational-cum-computational models of the mind—a symbolic model and a networks or connectionist one—and their pros and cons. Based on this we then outline a radical, non-representational and non-computational alternative model that has been gaining ground recently, and which has significant affinities with complexity explanations in (...)
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  • Approaches to learning and representation.Pat Langley - 1990 - Behavioral and Brain Sciences 13 (3):500-501.
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  • What can psychologists learn from hidden-unit nets?K. Lamberts & G. D'Ydewalle - 1990 - Behavioral and Brain Sciences 13 (3):499-500.
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  • How connectionist models learn: The course of learning in connectionist networks.John K. Kruschke - 1990 - Behavioral and Brain Sciences 13 (3):498-499.
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  • A non-empiricist perspective on learning in layered networks.Michael I. Jordan - 1990 - Behavioral and Brain Sciences 13 (3):497-498.
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  • But what is the substance of connectionist representation?James Hendler - 1990 - Behavioral and Brain Sciences 13 (3):496-497.
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  • What connectionist models learn: Learning and representation in connectionist networks.Stephen José Hanson & David J. Burr - 1990 - Behavioral and Brain Sciences 13 (3):471-489.
    Connectionist models provide a promising alternative to the traditional computational approach that has for several decades dominated cognitive science and artificial intelligence, although the nature of connectionist models and their relation to symbol processing remains controversial. Connectionist models can be characterized by three general computational features: distinct layers of interconnected units, recursive rules for updating the strengths of the connections during learning, and “simple” homogeneous computing elements. Using just these three features one can construct surprisingly elegant and powerful models of (...)
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  • Learning and representation: Tensions at the interface.Steven José Hanson - 1990 - Behavioral and Brain Sciences 13 (3):511-518.
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  • Expose hidden assumptions in network theory.Karl Haberlandt - 1990 - Behavioral and Brain Sciences 13 (3):495-496.
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