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Active Symbols and Internal Models: Towards a Cognitive Connectionism

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Connectionism in Context

Part of the book series: Artificial Intelligence and Society ((HCS))

Abstract

There can be little doubt that the connectionist revolution is under way. In the last five years, the class of techniques that fall under the collective heading of “connectionism” has become the single most credible competitor to three decades of research in artificial intelligence (AI). Originally a response to the failures of the “symbolic” paradigm to live up to the expectations of the 1960s and 1970s, connectionist networks have shown promise in areas such as object recognition, pattern completion, speech synthesis and verb conjugation. However, these achievements do not, in and of themselves, constitute revolutionary advances in Al. Their real importance lies not so much in the results, but rather in the means used to achieve them.

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Authors
  1. Stephen Kaplan
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  2. Mark Weaver
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  3. Robert M. French
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Editor information

Editors and Affiliations

  1. School of Cognitive and Computing Sciences, University of Sussex, Falmer, Brighton, BN1 9QH, UK

    Andy Clark  & Rudi Lutz  & 

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© 1992 Springer-Verlag London Limited

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Kaplan, S., Weaver, M., French, R.M. (1992). Active Symbols and Internal Models: Towards a Cognitive Connectionism. In: Clark, A., Lutz, R. (eds) Connectionism in Context. Artificial Intelligence and Society. Springer, London. https://doi.org/10.1007/978-1-4471-1923-4_6

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  • DOI: https://doi.org/10.1007/978-1-4471-1923-4_6

  • Publisher Name: Springer, London

  • Print ISBN: 978-3-540-19716-4

  • Online ISBN: 978-1-4471-1923-4

  • eBook Packages: Springer Book Archive

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