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A Monte-Carlo Path Planner for Dynamic and Partially Observable Environments

Naveed, Munir, Kitchin, Diane E., Crampton, Andrew, Chrpa, Lukáš and Gregory, Peter (2012) A Monte-Carlo Path Planner for Dynamic and Partially Observable Environments. In: Computational Intelligence and Games (CIG), 2012 IEEE Conference on. IEEE Computational Intelligence Society, pp. 211-218. ISBN 9781467311939

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    Abstract

    In this paper, we present a Monte-Carlo policy rollout technique (called MOCART-CGA) for path planning in dynamic and partially observable real-time environments such as Real-time Strategy games. The emphasis is put on fast action selection motivating the use of Monte-Carlo techniques in MOCART-CGA. Exploration of the space is guided by using corridors which direct simulations in the neighbourhood of the best found moves.

    MOCART-CGA limits how many times a particular state-action pair is explored to balance exploration of the neighbourhood of the state and exploitation of promising actions. MOCART-CGA is evaluated using four standard pathfinding benchmark maps, and over 1000 instances. The empirical results show that MOCART-CGA outperforms existing techniques, in terms of search time, in dynamic and partially observable environments. Experiments have also been performed in static (and partially observable) environments where MOCART-CGA still requires less time to search than its competitors, but typically finds lower quality plans.

    Item Type: Book Chapter
    Additional Information: © 2012 IEEE. Reprinted, with permission, from Naveed, Munir, Kitchin, Diane E., Crampton, Andrew, Chrpa, Lukáš and Gregory, Peter (2012) A Monte-Carlo Path Planner for Dynamic and Partially Observable Environments. IEEE Conference on Computational Intelligence and Games. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of University of Huddersfield products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org.
    Subjects: Q Science > Q Science (General)
    Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Q Science > QA Mathematics > QA76 Computer software
    Schools: School of Computing and Engineering
    School of Computing and Engineering > Informatics Research Group > Knowledge Engineering and Intelligent Interfaces
    Related URLs:
    Depositing User: Munir Naveed
    Date Deposited: 31 Jul 2012 12:06
    Last Modified: 05 Jun 2013 12:20
    URI: http://eprints.hud.ac.uk/id/eprint/14233

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