Adversarial Cooperative Path-Finding: Complexity and Algorithms

M. Ivanová, Pavel Surynek
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引用次数: 8

Abstract

The paper addresses a problem of adversarial cooperative path-finding (ACPF) which extends the well-studied problem of cooperative path-finding (CPF) with adversaries. In addition to cooperative path-finding where non-colliding paths for multiple agents connecting their initial positions and destinations are searched, consideration of agents controlled by the adversary is included in ACPF. This work is focused on both theoretical properties and practical solving techniques of the considered problem. We study computational complexity of the problem where we show that it is PSPACE-hard and belongs to the EXPTIME complexity class. Possible methods suitable for practical solving of the problem are introduced and thoroughly evaluated. Suggested solving approaches include greedy algorithms, minimax methods, Monte Carlo Tree Search, and adaptation of an algorithm for the cooperative version of the problem. Solving methods for ACPF were compared in a tournament in which all the pairs of suggested strategies were compared. Surprisingly frequent success rate of greedy methods and rather weaker results of Monte Carlo Tree Search were indicated by the conducted experimental evaluation.
对抗性合作寻径:复杂性和算法
本文研究了对抗性合作寻路(ACPF)问题,该问题扩展了已有研究的对抗性合作寻路(CPF)问题。除了搜索连接其初始位置和目的地的多个智能体的非冲突路径的合作寻径之外,ACPF还考虑了被对手控制的智能体。这项工作的重点是考虑问题的理论性质和实际解决技术。我们研究了这个问题的计算复杂度,我们证明了它是PSPACE-hard的,属于EXPTIME复杂度类。介绍了适用于实际解决问题的可能方法,并对其进行了全面评价。建议的解决方法包括贪心算法、极大极小法、蒙特卡罗树搜索,以及针对问题的合作版本的自适应算法。在比赛中比较了所有建议策略对的ACPF求解方法。实验结果表明,贪心方法的成功率高得惊人,而蒙特卡罗树搜索的结果却较弱。
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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