Traditional analytic or control-theoretic solutions to the problem of optimizing evasive maneuvers in the extended two-dimensional pursuer/evader problem require the evader to execute specific sequences of maneuvers at precise pursuer/evader distances. These solutions depend upon several pursuer-specific characteristics, and fail to effectively account for uncertainty about the state of the pursuer. This paper describes the implementation of a genetic programming system that evolves optimized solutions to the extended two-dimensional pursuer/evader problem that do not depend upon knowledge of the pursuer's current state. Best-of-run programs execute strategies by which an evader may maneuver to successfully evade a pursuer starting from a wide range of relative initial positions, under conditions where the state of the pursuer is unknown or uncertain.


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    Title :

    A new methodology for optimizing evasive maneuvers under uncertainty in the extended two-dimensional pursuer/evader problem


    Contributors:
    Moore, F.W. (author) / Garcia, O.N. (author)


    Publication date :

    1997


    Size :

    8 Seiten, 16 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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