【摘要】 遗传算法将其操作作用于一个称为染色体的位串上,通过复制、交叉、变异来产生个体之间的信息交换,并用适应度函数来度量个体在给定领域的性能,将遗传算法引入踢球行为控制, 实验表明,随着进化代数的增加,机器人对球的控制可以达到一种近似最优状态。更多还原

【Abstract】 Genetic algorithm is a kind of bionical optimized algorithm. It finds solution through simulating the learning procedure of natural evolution. It can be used in designing learning system of intelligent machines, independently or co - operated with other methods. Genetic algorithm acts on a string called chromosome, every bit of which is a gene. The individuals exchange information through reproduction, crossover and mutation. Fitness function is used to decide the quality of individual behavior. Since uncertainty exists in the environment of soccer - robots, genetic algorithm is introduced into the control of kick - ball behavior,so as to get a near - optimized solution. The result shows,the robots’control on the ball can arrive a near - optimized status with the growth of generations.更多还原