Hybrid evolutionary learning of fuzzy logic and genetic algorithm

Sung Bae Cho; Seung Ik Lee

doi:10.1007/bfb0028537

Hybrid evolutionary learning of fuzzy logic and genetic algorithm

Sung Bae Cho, Seung Ik Lee

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper presents a hybrid method of fuzzy logic and genetic algorithm as promising model for evolutionary system, which controls a mobile robot effectively. The system obtains sensory information from eight infrared sensors and operates the robot with two motors driven by fuzzy inference based on the sensory information. Genetic algorithm has been utilized to robustly determine the shape and number of membership functions in fuzzy rules. Through the simulation with a simulated robot called Khepera, we assure ourselves that the evolutionary approach finds a set of optimal fuzzy rules to make the robot reach the goal point, as well as to solve autonomously several subproblems such as obstacle avoidance and passing-by narrow corridors.

Original language	English
Title of host publication	Simulated Evolution and Learning - 1st Asia-Pacific Conference, SEAL 1996, Selected Papers
Editors	Xin Yao, Jong-Hwan Kim, Takeshi Furuhashi
Publisher	Springer Verlag
Pages	206-215
Number of pages	10
ISBN (Print)	3540633995, 9783540633990
DOIs	https://doi.org/10.1007/bfb0028537
Publication status	Published - 1997 Jan 1
Event	1st Asia-Pacific Conference on Simulated Evolution and Learning, SEAL 1996 - Taejon, Korea, Republic of Duration: 1996 Nov 9 → 1996 Nov 12

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	1285
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	1st Asia-Pacific Conference on Simulated Evolution and Learning, SEAL 1996
Country	Korea, Republic of
City	Taejon
Period	96/11/9 → 96/11/12

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/bfb0028537

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Cho, S. B., & Lee, S. I. (1997). Hybrid evolutionary learning of fuzzy logic and genetic algorithm. In X. Yao, J-H. Kim, & T. Furuhashi (Eds.), Simulated Evolution and Learning - 1st Asia-Pacific Conference, SEAL 1996, Selected Papers (pp. 206-215). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1285). Springer Verlag. https://doi.org/10.1007/bfb0028537

Cho, Sung Bae ; Lee, Seung Ik. / Hybrid evolutionary learning of fuzzy logic and genetic algorithm. Simulated Evolution and Learning - 1st Asia-Pacific Conference, SEAL 1996, Selected Papers. editor / Xin Yao ; Jong-Hwan Kim ; Takeshi Furuhashi. Springer Verlag, 1997. pp. 206-215 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "This paper presents a hybrid method of fuzzy logic and genetic algorithm as promising model for evolutionary system, which controls a mobile robot effectively. The system obtains sensory information from eight infrared sensors and operates the robot with two motors driven by fuzzy inference based on the sensory information. Genetic algorithm has been utilized to robustly determine the shape and number of membership functions in fuzzy rules. Through the simulation with a simulated robot called Khepera, we assure ourselves that the evolutionary approach finds a set of optimal fuzzy rules to make the robot reach the goal point, as well as to solve autonomously several subproblems such as obstacle avoidance and passing-by narrow corridors.",

author = "Cho, {Sung Bae} and Lee, {Seung Ik}",

year = "1997",

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booktitle = "Simulated Evolution and Learning - 1st Asia-Pacific Conference, SEAL 1996, Selected Papers",

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Cho, SB & Lee, SI 1997, Hybrid evolutionary learning of fuzzy logic and genetic algorithm. in X Yao, J-H Kim & T Furuhashi (eds), Simulated Evolution and Learning - 1st Asia-Pacific Conference, SEAL 1996, Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1285, Springer Verlag, pp. 206-215, 1st Asia-Pacific Conference on Simulated Evolution and Learning, SEAL 1996, Taejon, Korea, Republic of, 96/11/9. https://doi.org/10.1007/bfb0028537

Hybrid evolutionary learning of fuzzy logic and genetic algorithm. / Cho, Sung Bae; Lee, Seung Ik.

Simulated Evolution and Learning - 1st Asia-Pacific Conference, SEAL 1996, Selected Papers. ed. / Xin Yao; Jong-Hwan Kim; Takeshi Furuhashi. Springer Verlag, 1997. p. 206-215 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1285).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Cho SB, Lee SI. Hybrid evolutionary learning of fuzzy logic and genetic algorithm. In Yao X, Kim J-H, Furuhashi T, editors, Simulated Evolution and Learning - 1st Asia-Pacific Conference, SEAL 1996, Selected Papers. Springer Verlag. 1997. p. 206-215. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/bfb0028537