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International Conference on Evolvable Systems

ICES 2001: Evolvable Systems: From Biology to Hardware pp 192–203Cite as

Multi-agent Robot Learning by Means of Genetic Programming: Solving an Escape Problem

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2210))

Abstract

This paper presents the emergence of the cooperative behavior for multiple robot agents by means of Genetic Programming (GP). For this purpose, we utilize several extended mechanisms of GP, i.e., (1) a co-evolutionary breeding strategy, (2) a controlling strategy of introns, which are non-executed code segments dependent upon the situation, and (3) a subroutine discovery technique. Our experimental domain is an escape problem. We have chosen the actual experimental settings so as to be close to a real world as much as possible. The validness of our approach is discussed with comparative experiments using other methods, i.e., Q-learning and Neural networks, which shows the superiority of GP-based multi-agent learning.

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References

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Author information

Authors and Affiliations

  1. Dept. of Frontier Informatics, School of Frontier Science, The University of Tokyo, Tokyo

    Kohsuke Yanai & Hitoshi Iba

Authors
  1. Kohsuke Yanai
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  2. Hitoshi Iba
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Editor information

Editors and Affiliations

  1. University of Aizu, Tsuruga, Ikki-machi, Aizu-Wakamatsu City, Fukushima, 965-8580, Japan

    Yong Liu

  2. Faculty of Engineering, Shinshu University, 4-17-1 Wakasato, Nagano, 380-8553, Japan

    Kiyoshi Tanaka

  3. Nat. Inst. of Adv. Ind. Science and Technology, Adv. Semiconductor Research Center, AIST Tsukuba Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki, 305-8568, Japan

    Masaya Iwata  & Tetsuya Higuchi  & 

  4. University of Tsukuba, Institute of Information Sciences and Electronics, Tsukuba, Ibaraki, 305-8573, Japan

    Moritoshi Yasunaga

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© 2001 Springer-Verlag Berlin Heidelberg

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Yanai, K., Iba, H. (2001). Multi-agent Robot Learning by Means of Genetic Programming: Solving an Escape Problem. In: Liu, Y., Tanaka, K., Iwata, M., Higuchi, T., Yasunaga, M. (eds) Evolvable Systems: From Biology to Hardware. ICES 2001. Lecture Notes in Computer Science, vol 2210. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45443-8_17

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  • DOI: https://doi.org/10.1007/3-540-45443-8_17

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42671-4

  • Online ISBN: 978-3-540-45443-4

  • eBook Packages: Springer Book Archive

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