计算机博弈中估值算法与博弈训练的研究  

Study on Valuation Algorithm and Game Training in Computer Game

作　　者：吕艳辉[1] 宫瑞敏[1] 

机构地区：[1]沈阳理工大学信息科学与工程学院,沈阳110159

出　　处：《计算机工程》2012年第11期163-166,共4页Computer Engineering

基　　金：国家自然科学基金资助项目(60873010);新世纪优秀人才支持计划基金资助项目(NCET-05-0288)

摘　　要：计算机博弈程序难以处理局面估值问题。为此,结合时间差分算法和反向传播神经网络,设计一种局面估值算法BP-TD(),实现估值函数参数的自动调整。为提高博弈训练的性能,针对开局和中局,提出分阶段设置参数值的策略。以五子棋为应用背景,实现博弈系统RenjuTD。实验结果表明,该算法可使程序的博弈水平得到较大提高。Situation valuation is the most difficult issue in all kinds of computer game programs.A valuation method named BP-TD（？） is presented combining temporal difference algorithm and back propagation neural network,which can solve the problem of adjusting the parameter values of valuation function.On this basis,in order to enhance the performance of game training,the strategy of setting different parameter values is proposed for opening and middle game phases.The game system RenjuTD is implemented using Renju as application background.Experimental results show the game level of program is significantly improved.

关 键 词：计算机博弈 差分学习 反向传播神经网络 估值算法 增强学习 博弈训练 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]