期刊名称：Journal of Intelligent Learning Systems and Applications
印刷版ISSN：2150-8402
电子版ISSN：2150-8410
出版年度：2012
卷号：4
期号：3
页码：176-187
DOI：10.4236/jilsa.2012.43018
出版社：Scientific Research Publishing
摘要：In the case of on-line action role-playing game, the combat strategies can be divided into three distinct classes, Strategy of Motion(SM), Strategy of Attacking Occasion (SAO) and Strategy of Using Skill (SUS). In this paper, we analyze such strategies of a basic game model in which the combat is modeled by the discrete competitive Markov decision process. By introducing the chase model and the combat assistant technology, we identify the optimal SM and the optimal SAO, successfully. Also, we propose an evolutionary framework, including integration with competitive coevolution and cooperative coevolution, to search the optimal SUS pair which is regarded as the Nash equilibrium point of the strategy space. Moreover, some experiments are made to demonstrate that the proposed framework has the ability to find the optimal SUS pair. Furthermore, from the results, it is shown that using cooperative coevolutionary algorithm is much more efficient than using simple evolutionary algorithm.
