Abstract
In this paper, we propose a method to obtain strategy coalitions, whose confidences are adjusted by genetic algorithm to improve the generalization ability, in the process of co-evolutionary learning with a social game called Iterated Prisoner’s Dilemma (IPD) game. Experimental results show that several better strategies can be obtained through strategy coalition, and evolutionary optimization of the confidence for strategies within coalition improves the generalization ability.
| Original language | English |
|---|---|
| Title of host publication | New Frontiers in Artificial Intelligence - Joint JSAI 2001 Workshop Post-Proceedings |
| Publisher | Springer Verlag |
| Pages | 185-194 |
| Number of pages | 10 |
| Volume | 2253 |
| ISBN (Print) | 9783540455486 |
| Publication status | Published - 2001 Jan 1 |
| Event | 15th International Workshop on Japanese Society for Artificial Intelligence, JSAI 2001 - Matsue City, Japan Duration: 2001 May 20 → 2001 May 25 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 2253 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 15th International Workshop on Japanese Society for Artificial Intelligence, JSAI 2001 |
|---|---|
| Country | Japan |
| City | Matsue City |
| Period | 01/5/20 → 01/5/25 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
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Cooperative co-evolution of multi-agents. / Cho, Sung Bae.
New Frontiers in Artificial Intelligence - Joint JSAI 2001 Workshop Post-Proceedings. Vol. 2253 Springer Verlag, 2001. p. 185-194 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2253).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Cooperative co-evolution of multi-agents
AU - Cho, Sung Bae
PY - 2001/1/1
Y1 - 2001/1/1
N2 - In this paper, we propose a method to obtain strategy coalitions, whose confidences are adjusted by genetic algorithm to improve the generalization ability, in the process of co-evolutionary learning with a social game called Iterated Prisoner’s Dilemma (IPD) game. Experimental results show that several better strategies can be obtained through strategy coalition, and evolutionary optimization of the confidence for strategies within coalition improves the generalization ability.
AB - In this paper, we propose a method to obtain strategy coalitions, whose confidences are adjusted by genetic algorithm to improve the generalization ability, in the process of co-evolutionary learning with a social game called Iterated Prisoner’s Dilemma (IPD) game. Experimental results show that several better strategies can be obtained through strategy coalition, and evolutionary optimization of the confidence for strategies within coalition improves the generalization ability.
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UR - http://www.scopus.com/inward/citedby.url?scp=84974688594&partnerID=8YFLogxK
M3 - Conference contribution
SN - 9783540455486
VL - 2253
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 185
EP - 194
BT - New Frontiers in Artificial Intelligence - Joint JSAI 2001 Workshop Post-Proceedings
PB - Springer Verlag
ER -