TY - GEN
T1 - Evolutionary learning of multiagents using strategic coalition in the IPD game
AU - Yang, Seung Ryong
AU - Cho, Sung Bae
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2003.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2003
Y1 - 2003
N2 - Social and economic systems consist of complex interactions among its members. Their behaviors become adaptive according to changing environment. In many cases, an individual's behaviors can be modeled by a stimulus-response system in a dynamic environment. In this paper, we use the Iterated Prisoner's Dilemma (IPD) game, which is a simple model to deal with complex problems for dynamic systems. We propose strategic coalition consisting of many agents and simulate their emergence in a co-evolutionary learning environment. Also we introduce the concept of confidence for agents in a coalition and show how such confidences help to improve the generalization ability of the whole coalition. Experimental results show that co-evolutionary learning with coalitions and confidence can produce better performing strategies that generalize well in dynamic environments.
AB - Social and economic systems consist of complex interactions among its members. Their behaviors become adaptive according to changing environment. In many cases, an individual's behaviors can be modeled by a stimulus-response system in a dynamic environment. In this paper, we use the Iterated Prisoner's Dilemma (IPD) game, which is a simple model to deal with complex problems for dynamic systems. We propose strategic coalition consisting of many agents and simulate their emergence in a co-evolutionary learning environment. Also we introduce the concept of confidence for agents in a coalition and show how such confidences help to improve the generalization ability of the whole coalition. Experimental results show that co-evolutionary learning with coalitions and confidence can produce better performing strategies that generalize well in dynamic environments.
UR - http://www.scopus.com/inward/record.url?scp=9444223355&partnerID=8YFLogxK
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U2 - 10.1007/978-3-540-39896-7_5
DO - 10.1007/978-3-540-39896-7_5
M3 - Conference contribution
AN - SCOPUS:9444223355
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 50
EP - 61
BT - Intelligent Agents and Multi-Agent Systems
A2 - Lee, Jaeho
A2 - Barley, Mike
PB - Springer Verlag
T2 - 6th Pacific Rim International Workshop on Multi-Agents, PRIMA 2003
Y2 - 7 November 2003 through 8 November 2003
ER -