Learning Team Plays in a Competition for Foods between Ant Colonies as Autonomous Agents

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In this study, we approach the planning of the playing of team of games using an autonomous distributed system. In such environments, if planning takes time, it loses power and if we fail totake into account the factors of uncertainty, we can not deduce the successive the plan. During the games, the players will learn the team plays by try-and-error. For the learning, each player will acquire an opponents abilities and generate a that plan contains those uncertain factors implicitly.