alpha–beta pruning

E748469

Alpha–beta pruning is a search algorithm optimization that reduces the number of nodes evaluated in minimax-based game tree searches by eliminating branches that cannot affect the final decision.

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Statements (45)

Predicate Object
instanceOf adversarial search algorithm
game tree search technique
search algorithm optimization
alphaRepresents best value that maximizer can guarantee so far
alsoKnownAs alpha-beta search NERFINISHED
assumes deterministic game transitions
no hidden information
optimal play by both players
basedOn minimax algorithm
belongsTo algorithm design
artificial intelligence
benefitsFrom good move ordering
bestCaseComplexity O(b^(d/2))
betaRepresents best value that minimizer can guarantee so far
canBeCombinedWith heuristic evaluation functions
iterative deepening search
transposition tables
category depth-first search enhancement
commonlyAppliedIn computer Go variants with minimax search
computer Othello
computer checkers
computer chess
doesNotChange final minimax value with perfect play
eliminates branches that cannot affect final decision
enables deeper search within same time limit
ensures same decision as full minimax search if implemented correctly
formalizedBy John McCarthy NERFINISHED
goal reduce number of nodes evaluated in game tree search
improves search efficiency
influenced design of modern game-playing engines
introducedInContextOf game-playing programs
mathematicallyRelatedTo branch and bound
optimizes minimax-based game tree search
prunes subtrees that cannot improve current best outcome
prunesWhen alpha is greater than or equal to beta
reduces time complexity constant factor
requires two bounds alpha and beta
typicallyUsedWith depth-first minimax search
typicalUseCase searching game trees to a fixed depth with evaluation at leaves
usedIn perfect-information games
turn-based games
two-player zero-sum games
where b is branching factor
d is search depth
worstCaseComplexity O(b^d)

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Monte Carlo tree search relatedTo alpha–beta pruning