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Using Genetic Programming and Decision Trees for Team Evolution

This paper presents work done to evolve soccer strategies through Genetic Programming. Each agent is controlled by an algorithm in the form of a decision tree to act on the environment given its percepts. Several experiments were performed and an analysis of the performance of the algorithm was documented afterwards. Experimental results showed that it is possible to implement soccer learning in a multi-agent system through Genetic Programming, although the evolution of higher-level soccer strategies is a more difficult task.