Editing Alpha–beta pruning (section)

== Other algorithms ==
Since the [[minimax]] algorithm and its variants are inherently [[depth-first search|depth-first]], a strategy such as [[Iterative deepening depth-first search|iterative deepening]] is usually used in conjunction with alpha–beta so that a reasonably good move can be returned even if the algorithm is interrupted before it has finished execution. Another advantage of using iterative deepening is that searches at shallower depths give move-ordering hints, as well as shallow alpha and beta estimates, that both can help produce cutoffs for higher depth searches much earlier than would otherwise be possible.

Algorithms like [[SSS*]], on the other hand, use the [[best first search|best-first]] strategy.  This can potentially make them more time-efficient, but typically at a heavy cost in space-efficiency.<ref>{{citation|doi=10.1146/annurev.cs.02.060187.002315|title=Search techniques|journal=Annual Review of Computer Science|volume=2|pages=451–467|year=1987|first1=Judea|last1=Pearl|author1-link=Judea Pearl|first2=Richard|last2=Korf|author2-link=Richard E. Korf|quote=Like its A* counterpart for single-player games, SSS* is optimal in terms of the average number of nodes examined; but its superior pruning power is more than offset by the substantial storage space and bookkeeping required.}}</ref>