基于维数的实时策略博弈对手模型策略分类器

M. Aly, M. Aref, M.I. Hassan
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引用次数: 1

摘要

即时战略游戏是指两名或多名玩家在虚拟战场上操作,控制资源、建筑、单位和技术,通过摧毁他人来取得胜利的战略战争游戏。取得胜利取决于选择一个合适的计划(一套行动),选择一个合适的计划取决于对对手建立一个想象(建立一个模型)来知道如何应对。这种想象就是对手模型,对手建模过程越强,选择合适的方案就越准确,从而获得胜利的可能性就越高。即时策略游戏的环境挑战之一是,对手模型的分类是特定于游戏的。本文介绍了一种新的方法,通过这种方法,我们可以以一种非特定于游戏的方式对观察到的对手模型进行分类。我们的方法包含两条路径,每一种实时战略游戏类型(每一种训练过的对手模型)只执行一条路径,这意味着不同类型的实时战略游戏将执行我们方法的两条路径中的不同路径。
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Dimensions-based classifier for strategy classification of opponent models in real-time strategy games
Real-time strategy games are strategic war games where two or more players operate on a virtual battlefield, controlling resources, buildings, units and technologies to achieve victory by destroying others. Achieving victory depends on selecting a suitable plan (set of actions), selecting a suitable plan depends on building an imagination (building a model) of the opponent to know how to deal with. This imagination is the opponent model, the stronger the opponent modelling process is, the more accurate the selected suitable plan is and consequently the higher probability achieving the victory is. One of the environment's challenges in real-time strategy games is that classifying the opponent model is game specific. This paper introduces a new methodology through which we can classify the observed opponent model in a way that is not game specific. Our methodology includes two paths, only one of them is executed per real-time strategy game type (per opponent models trained), which means that different type of real-time strategy games will execute different paths of the two paths of our methodology.
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