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