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Currents in connectionism

Minds and Machines 3 (2):125-153 (1993)

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  1. Learning and applying contextual constraints in sentence comprehension.Mark F. St John & James L. McClelland - 1990 - Artificial Intelligence 46 (1-2):217-257.
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  • Minds, Brains, and Programs.John Searle - 2003 - In John Heil (ed.), Philosophy of Mind: A Guide and Anthology. New York: Oxford University Press.
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  • 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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  • Discovering Complexity: Decomposition and Localization as Strategies in Scientific Research.William Bechtel & Robert C. Richardson - 2010 - Princeton.
    An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in divergent (...)
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  • Discovering Complexity.William Bechtel, Robert C. Richardson & Scott A. Kleiner - 1996 - History and Philosophy of the Life Sciences 18 (3):363-382.
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  • Intrinsic intentionality.John Searle - 1980 - Behavioral and Brain Sciences 3 (3):450-457.
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  • Connectionism and the Mind: an Introduction to Parallel Processing in Networks.David Pickles, William Bechtel & Adele Abrahamson - 1992 - Philosophical Quarterly 42 (166):101.
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  • Finding Structure in Time.Jeffrey L. Elman - 1990 - Cognitive Science 14 (2):179-211.
    Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on processing rather than explicitly (as in a spatial representation). The current report develops a proposal along these lines first described by Jordan (1986) which involves the use of recurrent links in order to provide networks with a dynamic memory. In this approach, hidden unit patterns are fed back to themselves: (...)
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  • The sciences of the artificial.Herbert Alexander Simon - 1969 - [Cambridge,: M.I.T. Press.
    Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial ...
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  • On language and connectionism: Analysis of a parallel distributed processing model of language acquisition.Steven Pinker & Alan Prince - 1988 - Cognition 28 (1-2):73-193.
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  • 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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  • Minds, brains, and programs.John Searle - 1980 - Behavioral and Brain Sciences 3 (3):417-57.
    What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...)
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  • Analog retrieval by constraint satisfaction.Paul Thagard, Keith J. Holyoak, Greg Nelson & David Gochfeld - 1990 - Artificial Intelligence 46 (3):259-310.
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  • GE Hinton, and T. J. Sejnowski," A learning machine for Boltzman Machines,".D. H. Ackley - 1985 - Cognitive Science 9 (1):147-169.
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  • A Distributed Connectionist Production System.David S. Touretzky & Geoffrey E. Hinton - 1988 - Cognitive Science 12 (3):423-466.
    DCPS is a connectionist production system interpreter that uses distributed representations. As a connectionist model it consists of many simple, richly interconnected neuron‐like computing units that cooperate to solve problems in parallel. One motivation for constructing DCPS was to demonstrate that connectionist models are capable of representing and using explicit rules. A second motivation was to show how “coarse coding” or “distributed representations” can be used to construct a working memory that requires far fewer units than the number of different (...)
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  • A learning algorithm for boltzmann machines.David H. Ackley, Geoffrey E. Hinton & Terrence J. Sejnowski - 1985 - Cognitive Science 9 (1):147-169.
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  • Tensor product variable binding and the representation of symbolic structures in connectionist systems.Paul Smolensky - 1990 - Artificial Intelligence 46 (1-2):159-216.
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  • Recursive distributed representations.Jordan B. Pollack - 1990 - Artificial Intelligence 46 (1-2):77-105.
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  • {Finding structure in time}.J. Elman - 1993 - {Cognitive Science} 48:71-99.
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  • A sceptical theory of inheritance in nonmonotonic semantic networks.John F. Horty, Richmond H. Thomason & David S. Touretzky - 1990 - Artificial Intelligence 42 (2-3):311-348.
    inheritance reasoning in semantic networks allowing for multiple inheritance with exceptions. The approach leads to a definition of iaheritance that is..
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  • Compositionality: A connectionist variation on a classical theme.Tim van Gelder - 1990 - Cognitive Science 14 (3):355-384.
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  • Compositionality: A connectionist variation on a classical theme.Tim van Gelder - 1990 - Cognitive Science 14 (3):355-84.
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  • BoltzCONS: Dynamic symbol structures in a connectionist network.David S. Touretzky - 1990 - Artificial Intelligence 46 (1-2):5-46.
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  • U-shaped learning and frequency effects in a multi-layered perception: Implications for child language acquisition.Kim Plunkett & Virginia Marchman - 1991 - Cognition 38 (1):43-102.
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  • Natural Language Processing With Modular Pdp Networks and Distributed Lexicon.Risto Miikkulainen & Michael G. Dyer - 1991 - Cognitive Science 15 (3):343-399.
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  • Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks.Robert A. Jacobs, Michael I. Jordan & Andrew G. Barto - 1991 - Cognitive Science 15 (2):219-250.
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  • M. 1. Jordan, and AG Barto. Task decomposition through competition in a modular connectionist architecture: The what and where vision task. [REVIEW]Robert A. Jacobs - 1990 - Cognitive Science 15 (2):219-250.
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  • Analogical Mapping by Constraint Satisfaction.Keith J. Holyoak & Paul Thagard - 1989 - Cognitive Science 13 (3):295-355.
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  • Connectionist learning procedures.Geoffrey E. Hinton - 1989 - Artificial Intelligence 40 (1-3):185-234.
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  • Compositionality: A Connectionist Variation on a Classical Theme.Tim Gelder - 1990 - Cognitive Science 14 (3):355-384.
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  • Tensor Manipulation Networks: Connectionist and Symbolic Approaches to Comprehension, Learning, and Planning.Charles Patrick Dolan - 1989 - Dissertation, University of California, Los Angeles
    It is a controversial issue as to which of the two approaches, the Physical Symbol System Hypothesis or Parallel Distributed Processing , is a better characterization of the mind. At the root of this controversy are two questions: What sort of computer is the brain, and what sort of programs run on that computer? What is presented here is a theory which bridges the apparent gap between PSSH and PDP approaches. In particular, a computer is presented that adheres to constraints (...)
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  • Exploring the symbolic/subsymbolic continuum: A case study of RAAM.Douglas S. Blank, Lisa A. Meeden & James B. Marshall - 1992 - In John Dinsmore (ed.), The Symbolic and Connectionist Paradigms: Closing the Gap. Lawrence Erlbaum. pp. 113--148.
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