A comparison of team evolution operators | IEEE Conference Publication | IEEE Xplore

A comparison of team evolution operators


Abstract:

One of the main research topics in multi-agent systems is learning cooperation among agents. In the MARLBS system, we use genetic algorithms to evolve neural networks, wh...Show More

Abstract:

One of the main research topics in multi-agent systems is learning cooperation among agents. In the MARLBS system, we use genetic algorithms to evolve neural networks, which enhances the cooperation between agents. In this paper, we examine several evolutionary operators to evolve a team, in which team members cooperate with each other to solve problems. The best operators found from experiments efficiently reduce learning time.
Date of Conference: 24-24 September 2004
Date Added to IEEE Xplore: 18 October 2004
Print ISBN:0-7695-2101-0
Conference Location: Beijing, China

References

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