Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Introduction and Improvement of Genetic Programming for Intelligent Fuzzy Robots

  • Murai, Yasuyuki (Department of Information and Computer sciences, Kanagawa Institute of Technology) ;
  • Matsumura, Koki (Department of Information and Knowledge Engineering, Tottori University) ;
  • Tatsumi, Hisayuki (Department of Computer Science, Tsukuba College of Technology) ;
  • Tsuji, Hiroyuki (Department of Information and Computer sciences, Kanagawa Institute of Technology) ;
  • Tokumasu, Shinji (Department of Information and Computer sciences, Kanagawa Institute of Technology)
  • Published : 2003.09.01
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Abstract

We've been following research on the obstacle avoidance that is based on fuzzy control. We previously proposed a new method of automatically generating membership functions, which play an important role in improving accuracy of fuzzy control, by using genetic programming (GP). In this paper, we made two improvements to our proposed method, for the purpose of achieving better intelligence in fuzzy robots. First, the mutation rate is made to change dynamically, according to the coupled chaotic system. Secondly, the population partitioning using deme is introduced by parallel processing. The effectiveness of these improvements is demonstrated through several computer simulations.

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