Elsevier

Fuzzy Sets and Systems

Volume 82, Issue 2, 9 September 1996, Pages 235-251
Fuzzy Sets and Systems

A Prolog-like inference system based on neural logic — An attempt towards fuzzy neural logic programming

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Abstract

Research under the name of Neural Logic Networks is an attempt to integrate connectionist models and logic reasoning [8, 9]. With a Neural Logic Network, a simple neural network structure with suitable weight(s) can be used to represent a set of flexible operations, which offer increased possibilities in dealing with inference in real-world problem solving. They also possess useful properties in an extended logic system which is called Neural Logic. One of the important features of Neural Logic is that all its operations can be defined and realized by neural networks, which form Neural Logic Networks. As one part of the research on Neural Logic Networks, fuzzy neural logic programming has been proposed [6]. This paper introduces a Prolog-like inference system based on Neural Logic as an implementation of fuzzy neural logic programming. In this system, fuzzy reasoning is executed by the Neural Logic inference engine with incomplete or uncertain knowledge. The framework of the system and its inference mechanism are described.

References (15)

  • A. Barr et al.
  • L. Ding

    A proposal of parallel resolution inference on neural logic network

  • L. Ding et al.

    Parallel fuzzy resolution inference on fuzzy neural logic network

  • L. Ding et al.

    A new method for approximate reasoning

  • L. Ding et al.

    Revision principle for approximate reasoning, based on linear revising method

  • L. Ding et al.

    The basic conception of fuzzy neural logic programming in fuzzy neural logic networks

  • T. Murata et al.

    A predicate-transition net model for parallel interpretation of logic programs

    IEEE Trans. Software Engng.

    (1988)
There are more references available in the full text version of this article.

Cited by (0)

1

Real World Computing Partnership.

2

Institute of Systems Science, National University of Singapore.

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