A cooperative behavior learning control of multi-robot using trace information

Tomofumi Ohshita, Ji Sun Shin, Michio Miyazaki, Hee Hyol Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The distributed autonomous robotic system has superiority of robustness and adaptability to dynamical environment, however, the system requires the cooperative behavior mutually for optimality of the system. The acquisition of action by reinforcement learning is known as one of the approaches when the multi-robot works with cooperation mutually for a complex task. This paper deals with the transporting problem of the multi-robot using Q-learning algorithm in the reinforcement learning. When a robot carries luggage, we regard it as that the robot leaves a trace to the own migrational path, which trace has feature of volatility, and then, the other robot can use the trace information to help the robot, which carries luggage. To solve these problems on multi-agent reinforcement learning, the learning control method using stress antibody allotment reward is used. Moreover, we propose the trace information of the robot to urge cooperative behavior of the multi-robot to carry luggage to a destination in this paper. The effectiveness of the proposed method is shown by simulation.

Original languageEnglish
Title of host publicationProceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08
Pages397-400
Number of pages4
Publication statusPublished - 2008 Dec 1
Event13th International Symposium on Artificial Life and Robotics, AROB 13th'08 - Oita, Japan
Duration: 2008 Jan 312008 Feb 2

Publication series

NameProceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08

Conference

Conference13th International Symposium on Artificial Life and Robotics, AROB 13th'08
CountryJapan
CityOita
Period08/1/3108/2/2

Keywords

  • Cooperative behavior
  • Multi-agent systems
  • Reinforcement learning
  • Stress antibody allotment reward

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

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  • Cite this

    Ohshita, T., Shin, J. S., Miyazaki, M., & Lee, H. H. (2008). A cooperative behavior learning control of multi-robot using trace information. In Proceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08 (pp. 397-400). (Proceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08).