Search and simulation in games and planning

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These are exciting times for research in heuristic search. Research goals that seemed completely out of reach just three years ago have been achieved through huge improvements in search techniques, and new applications have become possible. "Search and Simulation in Games and Planning" proposes research in the fast developing field of simulation-enhanced search methods. Statistical "Monte-Carlo" methods, which explore a search space by repeated random sampling, have proven to be a very powerful, dynamic technique that overcomes the limitations of more static previous approaches. These techniques have lead to rapid progress in applications as diverse as the ancient game of Go, game-independent General Game Playing, and even classical domain-independent planning.