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  1. Putting Knowledge in its Place: A Scheme for Programming Parallel Processing Structures on the Fly.James L. McClelland - 1985 - Cognitive Science 9 (1):113-146.
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  • Structure and Content in Language Production: A Theory of Frame Constraints in Phonological Speech Errors.Gary S. Dell, Cornell Juliano & Anita Govindjee - 1993 - Cognitive Science 17 (2):149-195.
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  • Dynamical Models of Sentence Processing.Whitney Tabor & Michael K. Tanenhaus - 1999 - Cognitive Science 23 (4):491-515.
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  • Arbib, M., Conklin, E., & Hill, J. From Schema Theory to Language.Suzanne Mannes - 1988 - Cognitive Science 12 (3):477-483.
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  • TSUNAMI: Simultaneous Understanding, Answering, and Memory Interaction for Questions.Scott P. Robertson - 1994 - Cognitive Science 18 (1):51-85.
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  • Semantic Boost on Episodic Associations: An Empirically‐Based Computational Model.Yaron Silberman, Shlomo Bentin & Risto Miikkulainen - 2007 - Cognitive Science 31 (4):645-671.
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  • A Bayesian‐Network Approach to Lexical Disambiguation.Leila M. R. Eizirik, Valmir C. Barbosa & Sueli B. T. Mendes - 1993 - Cognitive Science 17 (2):257-283.
  • A Computer Model of the Temporal Course of Agrammatic Sentence Understanding: The Effects of Variation in Severity and Sentence Complexity.Henk J. Haarmann & Herman H. J. Kolk - 1991 - Cognitive Science 15 (1):49-87.
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  • The Explanatory Role of Computation in Cognitive Science.Nir Fresco - 2012 - Minds and Machines 22 (4):353-380.
    Which notion of computation (if any) is essential for explaining cognition? Five answers to this question are discussed in the paper. (1) The classicist answer: symbolic (digital) computation is required for explaining cognition; (2) The broad digital computationalist answer: digital computation broadly construed is required for explaining cognition; (3) The connectionist answer: sub-symbolic computation is required for explaining cognition; (4) The computational neuroscientist answer: neural computation (that, strictly, is neither digital nor analogue) is required for explaining cognition; (5) The extreme (...)
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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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  • Form and Content in Semantics.Y. Wilks - 1990 - Synthese 82 (3):329-51.
    This paper continues a strain of intellectual complaint against the presumptions of certain kinds of formal semantics (the qualification is important) and their bad effects on those areas of artificial intelligence concerned with machine understanding of human language. After some discussion of the use of the term epistemology in artificial intelligence, the paper takes as a case study the various positions held by McDermott on these issues and concludes, reluctantly, that, although he has reversed himself on the issue, there was (...)
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  • Probability and Normativity.David Papineau - 1989 - Behavioral and Brain Sciences 12 (3):484-485.
  • Resources for Research on Analogy: A Multi-Disciplinary Guide.Marcello Guarini, Amy Butchart, Paul Simard Smith & Andrei Moldovan - 2009 - Informal Logic 29 (2):84-197.
    Work on analogy has been done from a number of disciplinary perspectives throughout the history of Western thought. This work is a multidisciplinary guide to theorizing about analogy. It contains 1,406 references, primarily to journal articles and monographs, and primarily to English language material. classical through to contemporary sources are included. The work is classified into eight different sections (with a number of subsections). A brief introduction to each section is provided. Keywords and key expressions of importance to research on (...)
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  • 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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  • Connectionism and Interlevel Relations.William Bechtel - 1988 - Behavioral and Brain Sciences 11 (1):24-25.
  • Dynamic Context Generation for Natural Language Understanding: A Multifaceted Knowledge Approach.Samuel W. K. Chan - unknown
    ��We describe a comprehensive framework for text un- derstanding, based on the representation of context. It is designed to serve as a representation of semantics for the full range of in- terpretive and inferential needs of general natural language pro- cessing. Its most distinctive feature is its uniform representation of the various simple and independent linguistic sources that play a role in determining meaning: lexical associations, syntactic re- strictions, case-role expectations, and most importantly, contextual effects. Compositional syntactic structure from a (...)
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  • Crossing the Associative/Inferential Divide: Ad Hoc Concepts and the Inferential Power of Schemata.Marco Mazzone - 2014 - Review of Philosophy and Psychology 5 (4):583-599.
    How do we construct ad hoc concepts, especially those characterised by emergent properties? A reasonable hypothesis, suggested both in psychology and in pragmatics , is that some sort of inferential processing must be involved. I argue that this inferential processing can be accounted for in associative terms. My argument is based on the notion of inference as associative pattern completion based on schemata, with schemata being conceived in turn as patterns of concepts and their relationships. The possible role of conscious (...)
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  • Automatic Indexing Based on Term Activity語の活性度に基づくキーワード抽出法.Naohiro Matsumura, Yukio Ohsawa & Mitsuru Ishizuka - 2002 - Transactions of the Japanese Society for Artificial Intelligence 17:398-406.
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  • The Role of Knowledge in Discourse Comprehension: A Construction-Integration Model.Walter Kintsch - 1988 - Psychological Review 95 (2):163-182.
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  • Explanatory Coherence (Plus Commentary).Paul Thagard - 1989 - Behavioral and Brain Sciences 12 (3):435-467.
    This target article presents a new computational theory of explanatory coherence that applies to the acceptance and rejection of scientific hypotheses as well as to reasoning in everyday life, The theory consists of seven principles that establish relations of local coherence between a hypothesis and other propositions. A hypothesis coheres with propositions that it explains, or that explain it, or that participate with it in explaining other propositions, or that offer analogous explanations. Propositions are incoherent with each other if they (...)
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  • On the Proper Treatment of Connectionism.Paul Smolensky - 1988 - Behavioral and Brain Sciences 11 (1):1-23.
    A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...)
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  • Putting Together Connectionism – Again.Paul Smolensky - 1988 - Behavioral and Brain Sciences 11 (1):59-74.
    A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...)
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  • New Science for Old.Bruce Mangan & Stephen Palmer - 1989 - Behavioral and Brain Sciences 12 (3):480-482.
  • A Capacity Theory of Comprehension: Individual Differences in Working Memory.Marcel A. Just & Patricia A. Carpenter - 1992 - Psychological Review 99 (1):122-149.
  • The Reality of the Symbolic and Subsymbolic Systems.Andrew Woodfield & Adam Morton - 1988 - Behavioral and Brain Sciences 11 (1):58-58.
  • Has the Case Been Made Against the Ecumenical View of Connectionism?Robert Van Gulick - 1988 - Behavioral and Brain Sciences 11 (1):57-58.
  • The Essential Opacity of Modular Systems: Why Even Connectionism Cannot Give Complete Formal Accounts of Cognition.Marten J. den Uyl - 1988 - Behavioral and Brain Sciences 11 (1):56-57.
  • On the Proper Treatment of Thermostats.David S. Touretzky - 1988 - Behavioral and Brain Sciences 11 (1):55-56.
    A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...)
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  • From Data to Dynamics: The Use of Multiple Levels of Analysis.Gregory O. Stone - 1988 - Behavioral and Brain Sciences 11 (1):54-55.
  • From Connectionism to Eliminativism.Stephen P. Stich - 1988 - Behavioral and Brain Sciences 11 (1):53-54.
  • How Fully Should Connectionism Be Activated? Two Sources of Excitation and One of Inhibition.Roger N. Shepard - 1988 - Behavioral and Brain Sciences 11 (1):52-52.
  • Structure and Controlling Subsymbolic Processing.Walter Schneider - 1988 - Behavioral and Brain Sciences 11 (1):51-52.
  • Making the Connections.Jay G. Rueckl - 1988 - Behavioral and Brain Sciences 11 (1):50-51.
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  • Sanity Surrounded by Madness.Georges Rey - 1988 - Behavioral and Brain Sciences 11 (1):48-50.
  • A Two-Dimensional Array of Models of Cognitive Function.Gardner C. Quarton - 1988 - Behavioral and Brain Sciences 11 (1):48-48.
  • Subsymbols Aren't Much Good Outside of a Symbol-Processing Architecture.Alan Prince & Steven Pinker - 1988 - Behavioral and Brain Sciences 11 (1):46-47.
  • Connections Among Connections.R. J. Nelson - 1988 - Behavioral and Brain Sciences 11 (1):45-46.
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  • In Defence of Neurons.Chris Mortensen - 1988 - Behavioral and Brain Sciences 11 (1):44-45.
  • Epistemological Challenges for Connectionism.John McCarthy - 1988 - Behavioral and Brain Sciences 11 (1):44-44.
  • Symbols, Subsymbols, Neurons.William G. Lycan - 1988 - Behavioral and Brain Sciences 11 (1):43-44.
  • Connectionism in the Golden Age of Cognitive Science.Dan Lloyd - 1988 - Behavioral and Brain Sciences 11 (1):42-43.
  • Can This Treatment Raise the Dead?Robert K. Lindsay - 1988 - Behavioral and Brain Sciences 11 (1):41-42.
  • Physics, Cognition, and Connectionism: An Interdisciplinary Alchemy.Wendy G. Lehnert - 1988 - Behavioral and Brain Sciences 11 (1):40-41.
  • Smolensky, Semantics, and the Sensorimotor System.George Lakoff - 1988 - Behavioral and Brain Sciences 11 (1):39-40.
  • On the Obvious Treatment of Connectionism.Stephen José Hanson - 1988 - Behavioral and Brain Sciences 11 (1):38-39.
  • Some Memory, but No Mind.Lawrence E. Hunter - 1988 - Behavioral and Brain Sciences 11 (1):37-38.
  • Common Sense and Conceptual Halos.Douglas R. Hofstadter - 1988 - Behavioral and Brain Sciences 11 (1):35-37.
  • Statistical Rationality.Richard M. Golden - 1988 - Behavioral and Brain Sciences 11 (1):35-35.
  • Connectionism and the Study of Language.R. Freidin - 1988 - Behavioral and Brain Sciences 11 (1):34-35.
  • Dynamic Systems and the “Subsymbolic Level”.Walter J. Freeman - 1988 - Behavioral and Brain Sciences 11 (1):33-34.