Cooperative RoboCup agents using genetic case-based reasoning

RoboCup soccer game is a competition game. Robots need good strategy and planning ability on different conditions to win the game. If robots act by prior rules, they cannot gain ground. In this paper, we proposed a hybrid approach to implement our RoboCup agent. It can provide good strategy for robots planning base on all kinds of conditions and saving experience for reusing. Robots will grow up by our hybrid approach without prior defining knowledge and complex math basis. They just learn by saving experience. The robots don´t only grow up but also avoid to making the same mistakes. And we show the effectiveness of the proposed method through implement and comparing with another learning approach.