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A Fuzzy Inference Network Model for Search Strategy Using Neural Logic Network

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Abstract

In this paper, a fuzzy inference network model for search strategy using neural logic network is presented. The model describes search strategy, and neural logic network is used to search. Fuzzy logic can bring about appropriate inference results by ignoring some information in the reasoning process. Neural logic networks are powerful tools for the reasoning process but not appropriate for the logical reasoning. To model human knowledge, besides the reasoning process capability, the logical reasoning capability is equally important. Another new neural network called neural logic network is able to do the logical reasoning. Because the fuzzy inference is a fuzzy logical reasoning, we construct a fuzzy inference network model based on the neural logic network, extending the existing rule inference network. And the traditional propagation rule is modified.

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Authors and Affiliations

  1. Dept. of Multimedia Information & System, School of Multimedia, Yosu National University, San 96-1, Dunduckdong, Yosu, JunNam, 550-749, Korea

    Mal rey Lee

  2. Dept. of Information Communication Engineering, KunSan National University, Korea

    Jae Wan Lee

Authors
  1. Mal rey Lee
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  2. Jae Wan Lee
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Lee, M.r., Lee, J.W. A Fuzzy Inference Network Model for Search Strategy Using Neural Logic Network. Journal of Intelligent and Robotic Systems 36, 209–221 (2003). https://doi.org/10.1023/A:1022644001499

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