Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
MIKE: An Automatic Commentary System for Soccer
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
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In autonomous agents systems, each agent must behave independently according to its states and environments, and, if necessary, must cooperate with other agents in order to perform a given task. Therefore, each agent must incorporate learning and evolution in order to adapt to a dynamic environment. At present, in the field of multi-agent systems, methods by which to acquire the behavior rule from both expert knowledge and perception for an autonomous agent are generating a great deal of interest. In the present paper, we focused on the problem of "trash collection" by a multi-agent system and simulated the cooperative behavior of agents. Therefore, we investigated methods by which to learn the rules of cooperative behavior of multi-agents so as to solve problems effectively. We also used genetic algorithms (GA) as a method of acquiring the rules of an agent. Individual coding (definition of the rule) methods are performed, and the learning efficiency is evaluated.