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We apply the two-pluyer game assumprio~ls of 1i111ited search horizon and cornn~itnrent to nroves i constant time, to .single-agent heuristic search problems. We present a varicrtion of nrinimcr lookuhead search, and an analog to ulphu-betu pruning rlrot signijicantly improves the efficiency c. the algorithm. Paradoxically. the search horizon reachuble with… (More)

The complexities of various search algorithms are considered in terms of time, space, and cost of solution path. I t is known that breadth-first search requires too much space and depth-first search can use too much time and doesn't always find a cheapest path. A depth-first iteratiw-deepening algorithm is shown to be asymptotically optimal along all three… (More)

We have found the first optimal solutions to random instances of Rubik's Cube. The median optimal solution length appears to be 18 moves. The algorithm used is iterative-deepening-A* (IDA*), with a lower-bound heuristic function based on large memory-based lookup tables, or " pattern databases " (Culberson and Schaeffer 1996). These tables store the exact… (More)

We consider the case of heuristic search where the location of the goal may change during the course of the search. For example, the goal may be a target that is actively avoiding 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… (More)

Recently, best-first search algorithms have been introduced that store their nodes on disk, to avoid their inherent memory limitation. We introduce several improvements to the best of these, including parallel processing, to reduce their storage and time requirements. We also present a linear-time algorithm for bijectively mapping permutations to integers… (More)