single-jc.php

JACIII Vol.8 No.6 pp. 582-590
doi: 10.20965/jaciii.2004.p0582
(2004)

Paper:

Views over last 60 days: 600

Accelerated Genetic Programming for Intelligent Fuzzy Robots

Yasuyuki Murai*, Koki Matsumura**, Hisayuki Tatsumi***, Hiroyuki Tsuji*, and Shinji Tokumasu*

*Department of Information and Computer Sciences, Kanagawa Institute of Technology, 1030 Shimoogino, Atsugi, Kanagawa 243-0292, Japan

**Department of Information and Knowledge Engineering, Tottori University, 4-101 Koyama-Minami, Tottori, Tottori 680-8550, Japan

***Department of Computer Science, Tsukuba College of Technology, 4-12-7 Kasuga, Tsukuba, Ibaraki 305-0821, Japan

Received:
July 22, 2004
Accepted:
September 12, 2004
Published:
November 20, 2004
Creative Commons License
Keywords:
fuzzy, robot, genetic programming, coupled chaotic system,
Abstract

We previously proposed a new way of automatically generating membership functions that play an important role in improving the accuracy of fuzzy control by using genetic programming (GP). In this paper, we report 2 improvements for achieving better fuzzy robot intelligence. First, we made the mutation rate change dynamically based on a coupled chaotic system. Secondly, we introduced population partitioning using deme by parallel processing. The effectiveness of these improvements is demonstrated through computer simulation.

Cite this article as:
Y. Murai, K. Matsumura, H. Tatsumi, H. Tsuji, and S. Tokumasu, “Accelerated Genetic Programming for Intelligent Fuzzy Robots,” J. Adv. Comput. Intell. Intell. Inform., Vol.8, No.6, pp. 582-590, 2004.
Data files:

Creative Commons License  This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Aug. 17, 2022