@inproceedings{a52aa668085441f19330ad5e4f9a1fa5,
title = "Evolutionary learning of multiagents using strategic coalition in the IPD game",
abstract = "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.",
author = "Yang, {Seung Ryong} and Cho, {Sung Bae}",
year = "2003",
month = jan,
day = "1",
language = "English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "50--61",
editor = "Jaeho Lee and Mike Barley",
booktitle = "Intelligent Agents and Multi-Agent Systems",
address = "Germany",
note = "6th Pacific Rim International Workshop on Multi-Agents, PRIMA 2003 ; Conference date: 07-11-2003 Through 08-11-2003",
}