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<p><it>Abstract</it>—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.</p><p>The original MTS algorithm was constructed with the minimum operations necessary to guarantee its <it>completeness</it>, and hence is not very efficient. To improve its efficiency, we introduce ideas from the area of <it>resource-bounded planning</it> into MTS, including</p><l2><li><p><it>commitment to goals</it>, and</p></li><li><p><it>deliberation for selecting plans</it>.</p></li></l2><p>Experimental results demonstrate that the improved MTS is 10 to 20 times more efficient than the original MTS in uncertain situations.</p>
Search, real-time, problem solving, learning, moving target, deliberation, reactiveness, commitment.

T. Ishida and R. E. Korf, "Moving-Target Search: A Real-Time Search for Changing Goals," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 17, no. , pp. 609-619, 1995.
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