Learning for cooperation in multirobot team competitions

Kai-Tai Song, Chih Ching Tang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

We propose in this paper a learning architecture for cooperation in multirobot team competitions. This is a fully distributed, behavior-based software architecture, which facilitates flexible and reliable coordination on a team of robots performing tasks that may be subverted by another team of robots. Through the use of genetic algorithm, the robot team learns from past task execution experiences and improves its cooperation between the robots. The team performance in a game competition can be effectively improved. The feasibility of this architecture is demonstrated through simulation and practical experiments on a team of robots performing 3-on-3 robot soccer game.

Original languageEnglish
Title of host publicationProceedings - 2001 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Subtitle of host publicationIntegrating Intelligent Machines with Humans for a Better Tomorrow, CIRA 2001
EditorsHong Zhang, Peter Xiaoping Liu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages302-307
Number of pages6
ISBN (Electronic)0780372034
DOIs
StatePublished - 1 Jan 2001
EventIEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2001 - Banff, Canada
Duration: 29 Jul 20011 Aug 2001

Publication series

NameProceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA
Volume2001-January

Conference

ConferenceIEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2001
CountryCanada
CityBanff
Period29/07/011/08/01

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