Home > AI Searching Techniques > Best-First Search (Greedy Search)

Best-First Search (Greedy Search)

September 4, 2010 Leave a comment Go to comments

Best-first search is a search algorithm, which explores a graph by expanding the most promising node chosen according to a specified rule.

Judea Pearl described best-first search as estimating the promise of node n by a “heuristic evaluation function f(n) which, in general, may depend on the description of n, the description of the goal, the information gathered by the search up to that point, and most important, on any extra knowledge about the problem domain.”

Some authors have used “best-first search” to refer specifically to a search with a heuristic that attempts to predict how close the end of a path is to a solution, so that paths, which are judged closer to a solution, are extended first. This specific type of search is called greedy best-first search.

Efficient selection of the current best candidate for extension is typically implemented using a priority queue

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