基于遗传算法对奥赛罗问题的研究与改进

遗传算法是一种高效的最佳化的搜寻方法,具有简单、通用、鲁棒性强的特点,适合处理传统的搜索方法难以解决的复杂和非线性问题.利用遗传算法的思想,根据先验知识设计遗传算法初始群体产生方式和适应度函数,对传统的奥赛罗问题进行求解,并在传统遗传算法中加入自我调适的方法,来提高遗传算法的总体性能.在对这些问题进行研究的基础上,给出了大量的对比实验证明该算法是有效的,得出改进的遗传算法比传统遗传算法有更好的演化结果,并克服了传统遗传算法的早熟现象.

Genetic-Algorithm-Based Othello Problem's Study and Improvement

Genetic algorithm is a well - known efficient search method for the best. It has a lot of characteristics such as simplicity, universality and strong robustness, and is suitable for the complicated and nonlinear problems hard to be solved by traditional method. The paper designs the way of generating genetic algorithm initial group and fitness function according to a priori knowledge, uses genetic algorithm for solving the problem of the traditional Othello game and introduces a self - adaptive function for conventional genetic algorithm approach to improve the overall performance. Experimental results show that the genetic algorithm is better than the traditional genetic algorithm evolution, and can solve premature problem in the traditional genetic algorithm.