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Generating Strategies for Multi-Agent Pursuit-Evasion Games in Partially Observable Euclidean Space
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@MISC{Raboin_generatingstrategies,
author = {Eric Raboin and Ugur Kuter and Dana S. Nau},
title = {Generating Strategies for Multi-Agent Pursuit-Evasion Games in Partially Observable Euclidean Space},
year = {}
}
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Abstract
Abstract. We introduce a heuristic search technique for multi-agent pursuit-evasion games in partially observable Euclidean space where a team of tracker agents attempt to minimize their uncertainty about an evasive target agent. Agents ’ movement and observation capabilities are restricted by polygonal obstacles, while each agents ’ knowledge of the other agents is limited to direct observation or periodic updates from team members. Our polynomial-time algorithm is able to generate strategies for games in continuous two-dimensional Euclidean space, an improvement over past algorithms that were only applicable to simple gridworld domains. We show experimentally that our algorithm is tolerant of interruptions in communication between agents, continuing to generate good strategies despite long periods of time where agents are unable to communicate directly. Experimental results also show that our technique generates effective strategies quickly, with decision times of less than a second for reasonably sized domains with six or more agents.
Keyphrases
multi-agent pursuit-evasion game partially observable euclidean space tracker agent evasive target agent agent knowledge polygonal obstacle gridworld domain decision time long period direct observation good strategy heuristic search technique observation capability polynomial-time algorithm observable euclidean space team member continuous two-dimensional euclidean space agent movement technique generates effective strategy periodic update past algorithm experimental result
