New approaches to moving target search

Abstract

Abstract New methods for doing moving target search are presented. One algorithm, forgetful depth-first search, attempts to adapt the well-known depth-first algorithm to this problem domain. Also, a search technique called marking quickly acquires general knowledge about the search space. These methods are discussed and compared with other known methods. Experimental results show that forgetful depth-first search and marking give good performance. Introduction The moving target search problem and solutions to it were initially introduced by Korf and Ishida in their paper "Moving Target Search" Although the search problem and the algorithms that are discussed are applicable to any graph, the examples and experimentation presented in this paper uses grid type graphs with some of the nodes blocked-out to prevent passage. Such graphs allow for much variation and are commonly used for many search problems. With a moving target, heuristic functions take on the form h(a, b) -the predicted distance between states a and b. The research presented here generally assumes the existence of a reasonably good and admissible heuristic function. For the grid class of graphs Manhattan distance is used. The Euclidean distance can be used to break ties when multiple neighboring nodes have the same lowest heuristic. One simple moving target search algorithm is for the solver to get on the target's trail and follow it. This only works for "slower" targets. At the opposite end of the spectrum is Floyd's algorithm[3] which computes h* 0 in O(n 3) time. This algorithm can be revised to work by increasing the working matrix starting from 0 or initial heuristic). This makes the ntermediate computations useful (admissible). After this knowledge has been computed, the problem solver just f611ows the direct path to the target. This paper reviews the work of Korf and Ishida, introduces forgetful depth-first search and marking, and analyzes (with experimentation) the various algorithms. This paper shows that the new methods perform very well. Other Work 2.1 Korf and Ishida '91 In the paper "Moving Target Search" [1], Korf and Ishida introduce this search problem. In addition, they present an algorithm by which a problem solver can find the target. Original Moving Target Search Algorithm Their basic moving target search algorithm (BMTS) is an extension of the trivial "greedy" algorithm in which the problem solver always moves to adjacent node with lowest heuristic value (ties broken randomly). The reason it does not get stuck forever in a "local minimum&quot