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Despite recent progress in AI planning, many benchmarks remain challenging for current planners. In many domains, the performance of a planner can greatly be improved by discovering and exploiting information about the domain structure that is not explicitly encoded in the initial PDDL formulation. In this paper we present and compare two automated methods(More)
— FUEGO is both an open-source software framework and a state of the art program that plays the game of Go. The framework supports developing game engines for full-information two-player board games, and is used successfully in a substantial number of projects. The FUEGO Go program became the first program to win a game against a top professional player in(More)
With the recent success of Monte-Carlo tree search algorithms in Go and other games, and the increasing number of cores in standard CPUs, the efficient parallelization of the search has become an important issue. We present a new lock-free parallel algorithm for Monte-Carlo tree search which takes advantage of the memory model of the IA-32 and Intel-64 CPU(More)
The A* algorithm is the de facto standard used for pathfinding search. IDA* is a space-efficient version of A*, but it suffers from cycles in the search space (the price for using no storage), repeated visits to states (the overhead of iterative deepening), and a simplistic left-to-right traversal of the search tree. In this paper, the Fringe Search(More)
Pathfinding on a map is a fundamental problem in many applications, including robotics and computer games. Typically a grid is superimposed over the map where each cell in the grid forms a unique state. A state-space-based search algorithm, such as A* or IDA*, is then used for finding the optimal (shortest) path. In this paper we analyze the search behavior(More)
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