Results for 'connectionism'

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  1.  1
    George Graham.Connectionism in Pavlovtan Harness - 1991 - In Terence E. Horgan & John L. Tienson (eds.), Connectionism and the Philosophy of Mind. Kluwer Academic Publishers. pp. 143.
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  2.  3
    Jamd w, oarson.What Connectionists Cannot Do - 1991 - In Terence E. Horgan & John L. Tienson (eds.), Connectionism and the Philosophy of Mind. Kluwer Academic Publishers. pp. 113.
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  3. Connectionism, generalization, and propositional attitudes: A catalogue of challenging issues.John A. Barnden - 1992 - In John Dinsmore (ed.), The Symbolic and Connectionist Paradigms: Closing the Gap. Lawrence Erlbaum. pp. 149--178.
    [Edited from Conclusion section:] We have looked at various challenging issues to do with getting connectionism to cope with high-level cognitive activities such a reasoning and natural language understanding. The issues are to do with various facets of generalization that are not commonly noted. We have been concerned in particular with the special forms these issues take in the arena of propositional attitude processing. The main problems we have looked at are: (1) The need to construct explicit representations of (...)
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  4.  51
    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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  5.  43
    CAB: Connectionist Analogy Builder.Levi B. Larkey & Bradley C. Love - 2003 - Cognitive Science 27 (5):781-794.
    The ability to make informative comparisons is central to human cognition. Comparison involves aligning two representations and placing their elements into correspondence. Detecting correspondences is a necessary component of analogical inference, recognition, categorization, schema formation, and similarity judgment. Connectionist Analogy Builder (CAB) determines correspondences through a simple iterative computation that matches elements in one representation with elements playing compatible roles in the other representation while simultaneously enforcing structural constraints. CAB shows promise as a process model of comparison as its performance (...)
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  6.  76
    Connectionism and rules and representation systems: Are they compatible?William Bechtel - 1988 - Philosophical Psychology 1 (1):5-16.
    The introduction of connectionist or parallel distributed processing (PDP) systems to model cognitive functions has raised the question of the possible relations between these models and traditional information processing models which employ rules to manipulate representations. After presenting a brief account of PDP models and two ways in which they are commonly interpreted by those seeking to use them to explain cognitive functions, I present two ways one might relate these models to traditional information processing models and so not totally (...)
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  7. Connectionism and epistemology: Goldman on Winner-take-all networks.Paul Thagard - 1989 - Philosophia 19 (2-3):189-196.
    This paper examines Alvin Goldman's discussion of acceptance and uncertainty in chapter 15 of his book, Epistemology and Cognition. Goldman discusses how acceptance and rejection of beliefs might be understood in terms of "winner-take-all" connectionist networks. The paper answers some of the questions he raises in his epistemic evaluation of connectionist programs. The major tool for doing this is a connectionist model of explanatory coherence judgments (Thagard, Behavioral and Brain Sciences, 1989). Finally, there is a discussion of problems for Goldman's (...)
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  8. A connectionist theory of phenomenal experience.Jonathan Opie & Gerard O'Brien - 1999 - Behavioral and Brain Sciences 22 (1):127-148.
    When cognitive scientists apply computational theory to the problem of phenomenal consciousness, as many of them have been doing recently, there are two fundamentally distinct approaches available. Either consciousness is to be explained in terms of the nature of the representational vehicles the brain deploys; or it is to be explained in terms of the computational processes defined over these vehicles. We call versions of these two approaches _vehicle_ and _process_ theories of consciousness, respectively. However, while there may be space (...)
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  9.  97
    Connectionism and the Philosophy of Psychology.Terence Horgan & John Tienson - 1996 - MIT Press.
    In Connectionism and the Philosophy of Psychology, Horgan and Tienson articulate and defend a new view of cognition.
  10. Connectionism and the Intentionality of the Programmer.Mark Ressler - 2003 - Dissertation, San Diego State University
    Connectionism seems to avoid many of the problems of classical artificial intelligence, but has it avoided all of them? In this thesis I examine the problem that Intentionality, the directedness of thought to an object, raises for connectionism. As a preliminary approach, I consider the role of Intentionality in classical artificial intelligence from the programmer’s point of view. In this investigation, one problem I identify with classical artificial intelligence is that the Intentionality of the programmer seems to be (...)
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  11. Connectionism, systematicity, and the frame problem.W. F. G. Haselager & J. F. H. Van Rappard - 1998 - Minds and Machines 8 (2):161-179.
    This paper investigates connectionism's potential to solve the frame problem. The frame problem arises in the context of modelling the human ability to see the relevant consequences of events in a situation. It has been claimed to be unsolvable for classical cognitive science, but easily manageable for connectionism. We will focus on a representational approach to the frame problem which advocates the use of intrinsic representations. We argue that although connectionism's distributed representations may look promising from this (...)
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  12.  22
    Connectionism and the Mind: Parallel Processing, Dynamics, and Evolution in Networks.William Bechtel & Adele Abrahamsen - 2002 - Wiley-Blackwell.
    Connectionism and the Mind provides a clear and balanced introduction to connectionist networks and explores theoretical and philosophical implications. Much of this discussion from the first edition has been updated, and three new chapters have been added on the relation of connectionism to recent work on dynamical systems theory, artificial life, and cognitive neuroscience. Read two of the sample chapters on line: Connectionism and the Dynamical Approach to Cognition: http://www.blackwellpublishing.com/pdf/bechtel.pdf Networks, Robots, and Artificial Life: http://www.blackwellpublishing.com/pdf/bechtel2.pdf.
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  13.  30
    Connectionism and the Mind.William Bechtel & Adele Abrahamsen - 1991 - Wiley-Blackwell.
    Something remarkable is happening in the cognitive sciences. After a quarter of a century of cognitive models that were inspired by the metaphor of the digital computer, the newest cognitive models are inspired by the properties of the brain itself. Variously referred to as connectionist, parallel distributed processing, or neutral network models, they explore the idea that complex intellectual operations can be carried out by large networks of simple, neuron-like units. The units themselves are identical, very low-level and 'stupid'. Intelligent (...)
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  14.  97
    Connectionism, analogicity and mental content.Gerard O'Brien - 1998 - Acta Analytica 13:111-31.
    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 (...)
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  15. Concepts, connectionism, and the language of thought.Martin Davies - 1991 - In William Ramsey, Stephen P. Stich & D. M. Rumelhart (eds.), Philosophy and Connectionist Theory. Hillsdale, N.J.: Lawrence Erlbaum. pp. 485-503.
    The aim of this paper is to demonstrate a _prima facie_ tension between our commonsense conception of ourselves as thinkers and the connectionist programme for modelling cognitive processes. The language of thought hypothesis plays a pivotal role. The connectionist paradigm is opposed to the language of thought; and there is an argument for the language of thought that draws on features of the commonsense scheme of thoughts, concepts, and inference. Most of the paper (Sections 3-7) is taken up with the (...)
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  16. Connectionism, eliminativism, and the future of folk psychology.William Ramsey, Stephen P. Stich & J. Garon - 1991 - In William Ramsey, Stephen P. Stich & D. M. Rumelhart (eds.), Philosophy and Connectionist Theory. Hillsdale, N.J.: Lawrence Erlbaum. pp. 499-533.
  17. Connectionism and artificial intelligence: History and philosophical interpretation.Kenneth Aizawa - 1992 - Journal for Experimental and Theoretical Artificial Intelligence 4:1992.
    Hubert and Stuart Dreyfus have tried to place connectionism and artificial intelligence in a broader historical and intellectual context. This history associates connectionism with neuroscience, conceptual holism, and nonrationalism, and artificial intelligence with conceptual atomism, rationalism, and formal logic. The present paper argues that the Dreyfus account of connectionism and artificial intelligence is both historically and philosophically misleading.
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  18.  62
    Problems of Connectionism.Marta Vassallo, Davide Sattin, Eugenio Parati & Mario Picozzi - 2024 - Philosophies 9 (2):41.
    The relationship between philosophy and science has always been complementary. Today, while science moves increasingly fast and philosophy shows some problems in catching up with it, it is not always possible to ignore such relationships, especially in some disciplines such as philosophy of mind, cognitive science, and neuroscience. However, the methodological procedures used to analyze these data are based on principles and assumptions that require a profound dialogue between philosophy and science. Following these ideas, this work aims to raise the (...)
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  19.  84
    Connectionism and the fate of folk psychology: A reply to Ramsey, Stich and Garon.Malcolm Forster & Eric Saidel - 1994 - Philosophical Psychology 7 (4):437 – 452.
    Ramsey, Stick and Garon (1991) argue that if the correct theory of mind is some parallel distributed processing theory, then folk psychology must be false. Their idea is that if the nodes and connections that encode one representation are causally active then all representations encoded by the same set of nodes and connections are also causally active. We present a clear, and concrete, counterexample to RSG's argument. In conclusion, we suggest that folk psychology and connectionism are best understood as (...)
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  20. Symbolic connectionism in natural language disambiguation.James Franklin & S. W. K. Chan - 1998 - IEEE Transactions on Neural Networks 9:739-755.
    Uses connectionism (neural networks) to extract the "gist" of a story in order to represent a context going forward for the disambiguation of incoming words as a text is processed.
     
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  21. Connectionism, classical cognitive science and experimental psychology.Mike Oaksford, Nick Chater & Keith Stenning - 1990 - AI and Society 4 (1):73-90.
    Classical symbolic computational models of cognition are at variance with the empirical findings in the cognitive psychology of memory and inference. Standard symbolic computers are well suited to remembering arbitrary lists of symbols and performing logical inferences. In contrast, human performance on such tasks is extremely limited. Standard models donot easily capture content addressable memory or context sensitive defeasible inference, which are natural and effortless for people. We argue that Connectionism provides a more natural framework in which to model (...)
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  22. Connectionism, eliminativism, and the semantic view of theories.John Bickle - 1993 - Erkenntnis 39 (3):359-382.
    Recently some philosophers have urged that connectionist artificial intelligence is (potentially) eliminative for the propositional attitudes of folk psychology. At the same time, however, these philosophers have also insisted that since philosophy of science has failed to provide criteria distinguishing ontologically retentive from eliminative theory changes, the resulting eliminativism is not principled. Application of some resources developed within the semantic view of scientific theories, particularly recent formal work on the theory reduction relation, reveals these philosophers to be wrong in this (...)
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  23.  91
    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.  8
    Computationalism, Connectionism, and the Philosophy of Mind.Brian P. McLaughlin - 2003 - In Luciano Floridi (ed.), The Blackwell guide to the philosophy of computing and information. Blackwell. pp. 135–151.
    The prelims comprise: Introduction The Computational Theory of Mind The Symbol‐system Paradigm The Connectionist Computational Paradigm How are Paradigms Related?
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  25. 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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  26.  65
    Connectionist Models and Their Properties.J. A. Feldman & D. H. Ballard - 1982 - Cognitive Science 6 (3):205-254.
    Much of the progress in the fields constituting cognitive science has been based upon the use of explicit information processing models, almost exclusively patterned after conventional serial computers. An extension of these ideas to massively parallel, connectionist models appears to offer a number of advantages. After a preliminary discussion, this paper introduces a general connectionist model and considers how it might be used in cognitive science. Among the issues addressed are: stability and noise‐sensitivity, distributed decision‐making, time and sequence problems, and (...)
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  27.  42
    Connectionist and Memory‐Array Models of Artificial Grammar Learning.Zoltan Dienes - 1992 - Cognitive Science 16 (1):41-79.
    Subjects exposed to strings of letters generated by a finite state grammar can later classify grammatical and nongrammatical test strings, even though they cannot adequately say what the rules of the grammar are (e.g., Reber, 1989). The MINERVA 2 (Hintzman, 1986) and Medin and Schaffer (1978) memory‐array models and a number of connectionist outoassociator models are tested against experimental data by deriving mainly parameter‐free predictions from the models of the rank order of classification difficulty of test strings. The importance of (...)
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  28. The connectionist construction of concepts.Adrian Cussins - 1990 - In Margaret A. Boden (ed.), The Philosophy of Artificial Intelligence. Oxford, England: Oxford University Press.
    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.
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  29.  70
    Connectionist minds.Andy Clark - 1990 - Proceedings of the Aristotelian Society 90:83-102.
    Andy Clark; VI*—Connectionist Minds, Proceedings of the Aristotelian Society, Volume 90, Issue 1, 1 June 1990, Pages 83–102, https://doi.org/10.1093/aristotelia.
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  30.  67
    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 (...)
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  31.  47
    Connectionism, classical cognitivism and the relation between cognitive and implementational levels of analysis.Keith Butler - 1993 - Philosophical Psychology 6 (3):321-33.
    This paper discusses the relation between cognitive and implementational levels of analysis. Chalmers (1990, 1993) argues that a connectionist implementation of a classical cognitive architecture possesses a compositional semantics, and therefore undercuts Fodor and Pylyshyn's (1988) argument that connectionist networks cannot possess a compositional semantics. I argue that Chalmers argument misconstrues the relation between cognitive and implementational levels of analysis. This paper clarifies the distinction, and shows that while Fodor and Pylyshyn's argument survives Chalmers' critique, it cannot be used to (...)
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  32.  32
    Can Connectionists Explain Systematicity?Robert J. Matthews - 1997 - Mind and Language 12 (2):154-177.
    Classicists and connectionists alike claim to be able to explain systematicity. The proposed classicist explanation, I argue, is little more than a promissory note, one that classicists have no idea how to redeem. Smolensky's (1995) proposed connectionist explanation fares little better: it is not vulnerable to recent classicist objections, but it nonetheless fails, particularly if one requires, as some classicists do, that explanations of systematicity take the form of a‘functional analysis’. Nonetheless, there are, I argue, reasons for cautious optimism about (...)
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  33.  68
    Connectionism and the Philosophical Foundations of Cognitive Science.Terence 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: (1) the classical computation conception in cognitive science; (2) a popular foundational interpretation of connectionism that John Tienson and I call “non‐sentential computationalism”; and (3) an alternative interpretation of connectionism we call “dynamical cognition.” Also discussed are two recent (...)
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  34. 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 (...)
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  35.  48
    Connectionism and cognition: Why Fodor and Pylyshyn are wrong.James H. Fetzer - 1992 - In A. Clark & Ronald Lutz (eds.), Connectionism in Context. Springer Verlag. pp. 305-319.
  36.  39
    A Connectionist Approach to Knowledge Representation and Limited Inference.Lokendra Shastri - 1988 - Cognitive Science 12 (3):331-392.
    Although the connectionist approach has lead to elegant solutions to a number of problems in cognitive science and artificial intelligence, its suitability for dealing with problems in knowledge representation and inference has often been questioned. This paper partly answers this criticism by demonstrating that effective solutions to certain problems in knowledge representation and limited inference can be found by adopting a connectionist approach. The paper presents a connectionist realization of semantic networks, that is, it describes how knowledge about concepts, their (...)
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  37.  52
    Connectionism and the Philosophy of Mind.Terence E. Horgan & John L. Tienson (eds.) - 1991 - Kluwer Academic Publishers.
    "A third of the papers in this volume originated at the 1987 Spindel Conference ... at Memphis State University"--Pref.
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  38.  66
    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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  39. Connectionist Synthetic Epistemology: Requirements for the Development of Objectivity.Ron Chrisley & Andy Holland - unknown
    A connectionist system that is capable of learning about the spatial structure of a simple world is used for the purposes of synthetic epistemology: the creation and analysis of artificial systems in order to clarify philosophical issues that arise in the explanation of how agents, both natural and artificial, represent the world. In this case, the issues to be clarified focus on the content of representational states that exist prior to a fully objective understanding of a spatial domain. In particular, (...)
     
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  40.  32
    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 (...)
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  41. Connectionism and compositionality: Why Fodor and Pylyshyn were wrong.David J. Chalmers - 1993 - Philosophical Psychology 6 (3):305-319.
    This paper offers both a theoretical and an experimental perspective on the relationship between connectionist and Classical (symbol-processing) models. Firstly, a serious flaw in Fodor and Pylyshyn’s argument against connectionism is pointed out: if, in fact, a part of their argument is valid, then it establishes a conclusion quite different from that which they intend, a conclusion which is demonstrably false. The source of this flaw is traced to an underestimation of the differences between localist and distributed representation. It (...)
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  42. Philosophy and Connectionist Theory.William Ramsey, Stephen P. Stich & D. M. Rumelhart (eds.) - 1991 - Hillsdale, N.J.: 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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  43.  82
    Connectionism isn't magic.Hugh Clapin - 1991 - Minds and Machines 1 (2):167-84.
    Ramsey, Stich and Garon's recent paper Connectionism, Eliminativism, and the Future of Folk Psychology claims a certain style of connectionism to be the final nail in the coffin of folk psychology. I argue that their paper fails to show this, and that the style of connectionism they illustrate can in fact supplement, rather than compete with, the claims of a theory of cognition based in folk psychology's ontology. Ramsey, Stich and Garon's argument relies on the lack of (...)
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  44.  61
    A Connectionist Model of English Past Tense and Plural Morphology.Kim Plunkett & Patrick Juola - 1999 - Cognitive Science 23 (4):463-490.
    The acquisition of English noun and verb morphology is modeled using a single-system connectionist network. The network is trained to produce the plurals and past tense forms of a large corpus of monosyllabic English nouns and verbs. The developmental trajectory of network performance is analyzed in detail and is shown to mimic a number of important features of the acquisition of English noun and verb morphology in young children. These include an initial error-free period of performance on both nouns and (...)
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  45. Connectionism and cognitive architecture: A critical analysis.Jerry A. Fodor & Zenon W. Pylyshyn - 1988 - Cognition 28 (1-2):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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  46. Representations without rules, connectionism and the syntactic argument.Kenneth Aizawa - 1994 - 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 (...)
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  47.  88
    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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  48.  2
    Computationalism, Connectionism, and Kant’s Architectonic. 백승환 - 2024 - Modern Philosophy 23:87-131.
    본고는 오늘날의 철학적 화두인 인공지능 문제를 계산주의자들과 연결주의자들이 어떻게 상반되게 다루는 것인지를 검토한 후에 칸트의 건축술적 방법론에 기초해서 양자의 유의미한 절충을 기도한다. 첫째, 필자는 서양근대 철학사에서 완전히 반대됐던 두 입장들인 이성주의와 경험주의가 계산주의와 연결주의가 형성하는 긴장에 드러나고 있음에 주목하여, 비판기 칸트의 사유가 이성주의와 경험주의의 절충에서 실효를 보였듯이 크게 다르지 않게 계산주의와 연결주의의 절충에도 실효를 보일 것임을 주장한다. 둘째, 필자는 특히 양자에 공유되는 체계성과 조합성을 중심으로 삼아서 실제로 계산주의와 연결주의가 맞서는 상황을 단계별로 꼼꼼히 검토한다. 셋째, 칸트의 비판철학적 통찰을 구현하는 방법론인 건축술이 (...)
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  49.  13
    Aristotle, Connectionism, and the Morally Excellent Brain.David DeMoss - 1998 - The Paideia Archive: Twentieth World Congress of Philosophy 19:13-20.
    Can a mass of networked neurons produce moral human agents? I shall argue that it can; a brain can be morally excellent. A connectionist account of how the brain works can explain how a person might be morally excellent in Aristotle's sense of the term. According to connectionism, the brain is a maze of interconnections trained to recognize and respond to patterns of stimulation. According to Aristotle, a morally excellent human is a practically wise person trained in good habits. (...)
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  50.  63
    Computation, connectionism and modelling the mind.Mary Litch - 1997 - Philosophical Psychology 10 (3):357-364.
    Any analysis of the concept of computation as it occurs in the context of a discussion of the computational model of the mind must be consonant with the philosophic burden traditionally carried by that concept as providing a bridge between a physical and a psychological description of an agent. With this analysis in hand, one may ask the question: are connectionist-based systems consistent with the computational model of the mind? The answer depends upon which of several versions of connectionism (...)
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