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Moving-Target Search: A Real-Time Search for Changing Goals
June 1995 (vol. 17 no. 6)
pp. 609-619

Abstract—We consider the case of heuristic search where the goal may change during the course of the search. For example, the goal may be a target that actively avoids the problem solver. We present a moving-target search algorithm (MTS) to solve this problem. We prove that if the average speed of the target is slower than that of the problem solver, then the problem solver is guaranteed to eventually reach the target in a connected problem space.

The original MTS algorithm was constructed with the minimum operations necessary to guarantee its completeness, and hence is not very efficient. To improve its efficiency, we introduce ideas from the area of resource-bounded planning into MTS, including

  • commitment to goals, and

  • deliberation for selecting plans.

  • Experimental results demonstrate that the improved MTS is 10 to 20 times more efficient than the original MTS in uncertain situations.

    [1] M.E. Bratman,D.J. Israel,, and M. Pollack,“Plans and resource bounded practical reasoning,” Computational Intelligence, vol. 4, no. 4, pp. 349-355, 1988.
    [2] S.S. Brown,“Optimal search for a moving target in discrete time and space,” Operations Research, vol. 28, no. 6, pp. 1,275-1,289, 1980.
    [3] P.R. Cohen and H.J. Levesque,“Intention is choice with commitment,” Artificial Intelligence, vol. 42, no. 3, 1990.
    [4] J.M. Dobbie,“A two-cel model of search for a moving target,” Operations Research, vol. 22, pp. 79-92, 1974.
    [5] T. Dean and M. Boddy,“An analysis of time-dependent planning,” AAAI 88, pp. 49-54, 1988.
    [6] E.H. Durfee and V.R. Lesser,“Predictability versus responsiveness: Coordinating problem solvers in dynamic domains,” AAAI 88, pp. 66-71, 1988.
    [7] J.N. Eagle and J.R. Yee,“An optimal branch-and-bound procedure for the constrained path, moving target search problem,” Operations Research, vol. 38, no. 1, pp. 110-114, 1990.
    [8] M.P. Georgeff and A.L. Lansky,“Reactive reasoning and planning,” AAAI 87, pp. 677-682, 1987.
    [9] T. Ishida and R.E. Korf,“Moving target search,” IJCAI 91, pp. 204-210, 1991.
    [10] T. Ishida,“Moving target search with intelligence,” AAAI 92, pp. 525-532, 1992.
    [11] P.E. Hart,N.J. Nilsson,, and B. Raphael,“A formal basis for the heuristic determination of minimum cost paths,” IEEE Trans. Systems Science and Cybernetics, vol. 4, no. 2, pp. 100-107, 1968.
    [12] D.N. Kinny and M.P. Georgeff,“Commitment and effectiveness of situated agents,” IJCAI 91, pp. 82-88, 1991.
    [13] R.E. Korf,“Real-time heuristic search,” Artificial Intelligence, vol. 42, nos. 2-3, pp. 189-211, Mar. 1990.
    [14] J. Pearl, Heuristics: Intelligent Search Strategies for Computer Problem Solving, Addison-Wesley, Reading, Mass., 1984.
    [15] M.E. Pollack and M. Ringuette,“Introducing the Tileworld: Experimentally evaluating agent architectures,” AAAI 90, pp. 183-189, 1990.
    [16] S. Russell and E. Wefald, Do The Right Thing, MIT Press, 1991.
    [17] L. Tierney, and J.B. Kadane,“Surveillance search for a moving target,” Operations Research, vol. 31, pp. 720-783, 1983.
    [18] A.R. Washburn,“Search for a moving target: The FAB algorithm,” Operations Research, vol. 31, pp. 739-751, 1983.

    Index Terms:
    Search, real-time, problem solving, learning, moving target, deliberation, reactiveness, commitment.
    Citation:
    Toru Ishida, Richard E. Korf, "Moving-Target Search: A Real-Time Search for Changing Goals," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 17, no. 6, pp. 609-619, June 1995, doi:10.1109/34.387507
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