Search
نویسندگان
چکیده
AI efforts to solve problems with computers which humans routinely handle by employing innate cognitive abilities, pattern recognition, perception and experience, invariably must turn to considerations of search. This Chapter explores search methods in AI, including both blind exhaustive methods and informed heuristic and optimal methods, along with some more recent findings. The search methods covered include (for non-optimal, uninformed approaches) State-Space Search, Generate and Test, Means-ends Analysis, Problem Reduction, And/Or Trees, Depth First Search and Breadth First Search. Under the umbrella of heuristic (informed) methods we discuss are Hill Climbing, Best First Search, Bidirectional Search, and the A* Algorithm. Tree Searching algorithms for games have proven to be a rich source of study and provide empirical data about heuristic methods. Included here are the SSS* algorithm, variations on the alpha-beta minimax algorithm, and the use of iterative deepening.
منابع مشابه
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