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《Journal of Beijing University of Civil Engineering and Architecture》 2011-03
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Solution for the Maze Game Based on Multi-Agent Genetic Algorithm

Li Shaobao,Zhao Chunxiao(Department of Computer Teaching and Network Information,BUCEA Beijing 100044)  
The essence of game design is to design some related rules of the game.On the basis of the analysis of relationships among various elements in the maze game,a set of rules of the game is worked out abstractly in the paper.Then a multi-agent genetic algorithm,in which the individual of finding the maze's path is as an agent,is proposed.At last it is simulated by C++ and compared with the traditional genetic algorithm.The simulation results indicate that the proposed optimization model is reasonable and this algorithm can avoid precocious phenomena and have quicker convergence rate and better global astringency.
【CateGory Index】: TP18
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