Editing Best-first search (section)

{{Short description|Graph exploring search algorithm}}
'''Best-first search''' is a class of [[search algorithm]]s which explores a [[graph (data structure)|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 <math>f(n)</math> 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."<ref>[[Judea Pearl|Pearl, J.]] ''Heuristics: Intelligent Search Strategies for Computer Problem Solving''. Addison-Wesley, 1984. p. 48.</ref><ref name="RN03">
{{Cite book
| first1 = Stuart J. | last1 = Russell | author1-link = Stuart J. Russell
| first2 = Peter.    | last2 = Norvig  | author2-link = Peter Norvig
| title=[[Artificial Intelligence: A Modern Approach]]
| year = 2021
| edition = 4th 
| isbn = 9780134610993 
| lccn = 20190474
| publisher = Pearson | location = Hoboken
| pages = 73-74}}
</ref>

Some authors have used "best-first search" to refer specifically to a search with a [[Heuristic function|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. This specific type of search is called ''[[Greedy algorithm|greedy]] best-first search''<ref name="RN03"/> or ''pure heuristic search''.<ref>{{cite encyclopedia |first=Richard E. |last=Korf|author-link=Richard E. Korf |year=1999 |title=Artificial intelligence search algorithms |encyclopedia=Handbook of Algorithms and Theory of Computation |editor-first=Mikhail J. |editor-last=Atallah |publisher=CRC Press |isbn=0849326494}}</ref>

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

The [[A* search algorithm]] is an example of a best-first search algorithm, as is [[B*]]. Best-first algorithms are often used for path finding in [[combinatorial search]]. Neither A* nor B* is a greedy best-first search, as they incorporate the distance from the start in addition to estimated distances to the goal.