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General video game for 2 players: Framework and competition

机译:面向2位玩家的通用视频游戏:框架和竞争

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摘要

© 2016 IEEE. This paper presents a new track of the General Video Game AI competition for generic Artificial Intelligence agents, which features both competitive and cooperative real time stochastic two player games. The aim of the competition is to directly test agents against each other in more complex and dynamic environments, where there is an extra uncertainty in a game, consisting of the behaviour of the other player. The framework, server functionality and general competition setup are analysed and the results of the experiments with several sample controllers are presented. The results indicate that currently Open Loop Monte Carlo Tree Search is the overall leading algorithm on this set of games.
机译:©2016 IEEE。本文介绍了针对通用人工智能代理的通用视频游戏AI竞赛的新轨迹,其特点是具有竞争性和协作性的实时随机两种玩家游戏。比赛的目的是在更加复杂和动态的环境中直接测试坐席之间的竞争,在这种环境中,游戏中存在由其他玩家的行为组成的额外不确定性。分析了框架,服务器功能和一般竞赛设置,并给出了使用几个示例控制器的实验结果。结果表明,当前的“开环蒙特卡洛树搜索”是这组游戏的总体领先算法。

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