一种改进的分布式遗传算法在机器博弈中的应用研究

为提高机器博弈系统的智能水平，改善传统方法在静态评估参数组合优化训练中效率低下和训练结果质量不高的问题，提出一种分布式氏族遗传算子，从种群扩充方法和染色体复制的过程中实现了对自适应性遗传算法的改进.改进后的遗传算子在亲子代优良性状继承能力和基因表达的可解释性上有所提高，并在国际跳棋的优化实例中取得良好训练结果.通过仿真实验验证了所提出算法在处理一般性问题时性能稳定可靠. 

The Application Study on Improved Distributed Genetic Algorithm in Computer Games

In order to improve the intelligent of computer games (CGs) system, the efficiency of traditional methods in optimizing training of static evaluation parametric combination and the quality of training, a distributed genetic operator was proposed for clan crossover. The adaptive genetic algorithm was improved in the course of population enlarging and chromosome duplication. Analysis results show that, the ability has been improved with the improved genetic operators, to inherit superior character from parent generation and to explain gene expression. Better training results have been gained in actual optimization of draughts. Besides, simulation experiment has validated the stability and accountability of the algorithm in solving general problems.