Specialization of a UCT-Based General Game Playing Program to Single-Player Games

M. Świechowski, J. Mańdziuk, Y. Ong
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引用次数: 17

Abstract

General game playing (GGP) aims at designing autonomous agents capable of playing any game within a certain genre, without human intervention. GGP agents accept the rules, which are written in the logic-based game definition language (GDL) and unknown to them beforehand, at runtime. The state-of-the-art players use Monte Carlo tree search (MCTS) together with the upper confidence bounds applied to trees (UCT) method. In this paper, we discuss several enhancements to GGP players geared towards more effective playing of single-player games within the MCTS/UCT framework. The main proposed improvements include introduction of a collection of lightweight policies which can be used for guiding the MCTS and a GGP-friendly way of using transposition tables. We have tested our base player and a specialized version of it for single-player games in a series of experiments using ten single-player games of various complexity. It is clear from the results that the optimized version of the player achieves significantly better performance. Furthermore, in the same set of tests against publicly available version of CadiaPlayer, one of the strongest GGP agents, the results are also favorable to the enhanced version of our player.
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基于uct的通用游戏程序对单人游戏的专门化
通用游戏(General game playing, GGP)旨在设计能够在没有人为干预的情况下玩特定类型的任何游戏的自主代理。GGP代理在运行时接受用基于逻辑的游戏定义语言(GDL)编写的规则,并且事先不知道这些规则。最先进的球员使用蒙特卡洛树搜索(MCTS)和上置信限应用于树(UCT)方法。在本文中,我们讨论了GGP玩家在MCTS/UCT框架内更有效地玩单人游戏的几个增强功能。提出的主要改进包括引入一组可用于指导MCTS的轻量级策略,以及使用换位表的ggp友好方式。我们使用10款不同复杂度的单人游戏进行了一系列实验,测试了我们的基本玩家和专门的单人游戏版本。从结果中我们可以清楚地看到,优化后的玩家能够获得更好的表现。此外,在同一组测试中,针对公开版本的CadiaPlayer,最强的GGP代理之一,结果也有利于我们的播放器的增强版本。
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来源期刊
IEEE Transactions on Computational Intelligence and AI in Games
IEEE Transactions on Computational Intelligence and AI in Games COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, SOFTWARE ENGINEERING
CiteScore
4.60
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: Cessation. The IEEE Transactions on Computational Intelligence and AI in Games (T-CIAIG) publishes archival journal quality original papers in computational intelligence and related areas in artificial intelligence applied to games, including but not limited to videogames, mathematical games, human–computer interactions in games, and games involving physical objects. Emphasis is placed on the use of these methods to improve performance in and understanding of the dynamics of games, as well as gaining insight into the properties of the methods as applied to games. It also includes using games as a platform for building intelligent embedded agents for the real world. Papers connecting games to all areas of computational intelligence and traditional AI are considered.
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