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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 threeâ€¦ (More)

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 withâ€¦ (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 exactâ€¦ (More)

We describe a new technique for designing more accurate admissible heuristic evaluation functions, based on pattern databases 1]. While many heuristics, such as Manhattan distance, compute the cost of solving individual subgoals independently, pattern databases consider the cost of solving multiple subgoals simultaneously. Existing work on pattern databasesâ€¦ (More)

We explore a method for computing admissible heuristic evaluation functions for search problems. It utilizes pattern databases (Culberson & Schaeeer, 1998), which are precom-puted tables of the exact cost of solving various subproblems of an existing problem. Unlike standard pattern database heuristics, however, we partition our problems into disjointâ€¦ (More)