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Logic programs and connectionist networks

Authors
Journal
Journal of Applied Logic
1570-8683
Publisher
Elsevier
Publication Date
Volume
2
Issue
3
Identifiers
DOI: 10.1016/j.jal.2004.03.002
Keywords
  • Logic Programming
  • Metric Spaces
  • Connectionist Networks
Disciplines
  • Computer Science
  • Linguistics
  • Logic
  • Mathematics

Abstract

Abstract One facet of the question of integration of Logic and Connectionist Systems, and how these can complement each other, concerns the points of contact, in terms of semantics, between neural networks and logic programs. In this paper, we show that certain semantic operators for propositional logic programs can be computed by feedforward connectionist networks, and that the same semantic operators for first-order normal logic programs can be approximated by feedforward connectionist networks. Turning the networks into recurrent ones allows one also to approximate the models associated with the semantic operators. Our methods depend on a well-known theorem of Funahashi, and necessitate the study of when Funahashi's theorem can be applied, and also the study of what means of approximation are appropriate and significant.

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