Adaptive bots for real-time strategy games via map characterization

A. Fernández-Ares, P. García-Sánchez, A. García, J. J. M. Guervós
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引用次数: 19

Abstract

This paper presents a proposal for a fast on-line map analysis for the RTS game Planet Wars in order to define specialized strategies for an autonomous bot. This analysis is used to tackle two constraints of the game, as featured in the Google AI Challenge 2010: the players cannot store any information from turn to turn, and there is a limited action time of just one second. They imply that the bot must analyze the game map quickly, to adapt its strategy during the game. Based in our previous work, in this paper we have evolved bots for different types of maps. Then, all bots are combined in one, to choose the evolved strategy depending on the geographical configuration of the game in each turn. Several experiments have been conducted to test the new approach, which outperforms our previous version, based on an off-line general training.
基于地图特征的即时战略游戏的自适应机器人
本文提出了一种即时战略游戏《星球大战》的快速在线地图分析方法,以便为自主机器人定义专门的策略。这一分析用于解决游戏的两个限制因素,就像Google AI Challenge 2010所强调的那样:玩家不能从一个回合到另一个回合存储任何信息,并且只有一秒钟的有限行动时间。它们意味着bot必须快速分析游戏地图,以便在游戏过程中调整策略。基于我们之前的工作,在这篇论文中,我们为不同类型的地图进化了机器人。然后,所有的机器人结合在一起,在每个回合中根据游戏的地理配置选择进化的策略。已经进行了几个实验来测试新方法,该方法优于我们以前的版本,基于离线一般训练。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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