DocumentCode :
188495
Title :
Adversarial Cooperative Path-Finding: Complexity and Algorithms
Author :
Ivanova, Milena ; Surynek, Pavel
Author_Institution :
Charles Univ. Prague, Prague, Czech Republic
fYear :
2014
fDate :
10-12 Nov. 2014
Firstpage :
75
Lastpage :
82
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.
Keywords :
Monte Carlo methods; computational complexity; greedy algorithms; minimax techniques; multi-agent systems; tree searching; ACPF; EXPTIME complexity class; Monte Carlo tree search; PSPACE-hard; adversarial cooperative path-finding; computational complexity; greedy algorithms; greedy methods; minimax methods; multiple agents; noncolliding paths; Computational complexity; Cost accounting; Games; Joining processes; Monte Carlo methods; Standards; Monte Carlo Tree Search; PSPACE-hardness; adversaries; complexity; cooperative path-finding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference on
Conference_Location :
Limassol
ISSN :
1082-3409
Type :
conf
DOI :
10.1109/ICTAI.2014.22
Filename :
6984458
Link To Document :
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