Best-first search
Best-first search is a class of search algorithms which explores a regular undirected 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 ) {\displaystyle 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 importantly, 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 (or, goal), so that paths which are judged to be closer to a solution (or, goal) are expanded first.