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This involves two threshold parameter Alpha and beta for future expansion, so it is called alpha-beta pruning. It is also called as Alpha-Beta Algorithm . Alpha-beta pruning can be applied at any depth of a tree, and sometimes it not only prune the tree leaves but also entire sub-tree.
Jun 13, 2024 · Alpha-beta pruning is an optimization technique for the minimax algorithm. It reduces the number of nodes evaluated in the game tree by eliminating branches that cannot influence the final decision.
May 14, 2023 · Alpha Beta Pruning is an optimization technique of the Minimax algorithm. This algorithm solves the limitation of exponential time and space complexity in the case of the Minimax algorithm by pruning redundant branches of a game tree using its parameters Alpha( α \alpha α ) and Beta( β \beta β ).
D3.js web app for visualizing and understanding the Alpha-Beta Pruning algorithm. Developed for UC Berkeley's CS61B.
Alpha–beta pruning is a search algorithm that seeks to decrease the number of nodes that are evaluated by the minimax algorithm in its search tree. It is an adversarial search algorithm used commonly for machine playing of two-player combinatorial games ( Tic-tac-toe, Chess, Connect 4, etc.).
Mar 31, 2017 · In this article, we will go through the basics of the Minimax algorithm along with the functioning of the algorithm. We will also take a look at the optimization of the minimax algorithm, alpha-beta pruning.
Apr 10, 2021 · Alpha-beta pruning can provide performance optimization up to the square root of the performance of the original minimax algorithm. It may also provide no performance improvement at all, depending on how unlucky you are.
Alpha-beta pruning is the standard searching procedure used for solving 2-person perfect-information zero sum games exactly. Definitions: A position p. The value of a position p, f (p), is a numerical value computed from evaluating p. Value is computed from the root player’s point of view.
Lecture Videos. Lecture 6: Search: Games, Minimax, and Alpha-Beta. Description: In this lecture, we consider strategies for adversarial games such as chess. We discuss the minimax algorithm, and how alpha-beta pruning improves its efficiency. We then examine progressive deepening, which ensures that some answer is always available.
Avoiding searching a part of a tree is called pruning; this is an example of alpha-beta pruning. In general the minimax value of a node is going to be worth computing only if it lies within a particular range of values.
