Issues in Symbol Processing

Abstract

The notion of mind as symbol processor is fundamental to artificial intelligence and cognitive science, but some connectionists are now arguing against it. Eliminative connectionism challenges the validity of formal symbol manipulation as a level of mental description. We review some of the claims that have been made, and argue that most connectionist models, especially those constructed by learning algorithms, are operating at the level of pattern classifiers. Their (rather limited) success using non-symbolic representations demonstrates that they have not yet even approached the tasks which symbol processing models attempt to solve. Continued progress in connectionist research may require reimplementation rather than rejection of the symbolic level. (edc)

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Document Details

Document Type
Technical Report
Publication Date
Sep 29, 1987
Accession Number
ADA218941

Entities

People

  • David S. Touretzky

Organizations

  • Carnegie Mellon University

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  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Intelligence Software
  • Cognition
  • Cognitive Science
  • Computational Science
  • Computer Languages
  • Computer Science
  • Computers
  • Language
  • Linguistics
  • Machine Learning
  • Mental Processes
  • Neural Networks
  • Psychology
  • Reasoning
  • Security

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  • Artificial Intelligence
  • Software Engineering

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  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Machine Translation