## How does minimax alpha-beta pruning work?

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 games (Tic-tac-toe, Chess, Connect 4, etc.).

**What is alpha-beta pruning with example?**

Key points about alpha-beta pruning: The Max player will only update the value of alpha. The Min player will only update the value of beta. While backtracking the tree, the node values will be passed to upper nodes instead of values of alpha and beta. We will only pass the alpha, beta values to the child nodes.

### What is alpha-beta pruning Tutorialspoint?

Description. Aplha-Beta pruning is a optimization technique used in minimax algorithm. The idea benind this algorithm is cut off the branches of game tree which need not to be evaluated as better move exists already.

**What is the advantage of alpha-beta pruning to minimax algorithm?**

This algorithm is extremely beneficial, as it reduces the computation time and makes the search go deeper in the game tree, quickly. Moreover, Alpha Beta cutoff or prunes the evaluation in the game tree, when even a single possibility is found that proves the current move is worse than the previously examined move.

## What is the advantage of adding alpha-beta pruning to a minimax algorithm?

Alpha-Beta pruning is not actually a new algorithm, rather an optimization technique for minimax algorithm. It reduces the computation time by a huge factor. This allows us to search much faster and even go into deeper levels in the game tree.

**Why is it called alpha-beta pruning?**

It cuts off branches in the game tree which need not be searched because there already exists a better move available. It is called Alpha-Beta pruning because it passes 2 extra parameters in the minimax function, namely alpha and beta.

### What are advantages and disadvantages of alpha-beta pruning?

Using Alpha-Beta pruning is always beneficial, as it offers various benefits like better time complexity, over the minimax algorithm. However, there are still some drawbacks associated with this algorithm, which prevents it from being the ideal or the go-to search algorithm for all.

**What is the advantage of alpha-beta pruning?**

i) Alpha-beta pruning plays a great role in reducing the number of nodes which are found out by minimax algorithm. ii) When one chance or option is found at the minimum, it stops assessing a move. iii) This method also helps to improve the search procedure in an effective way.

## What are the advantages of alpha-beta pruning?

**What is the best case runtime of minimax using alpha-beta pruning?**

I understand the basics of minimax and alpha-beta pruning. In all the literature, they talk about the time complexity for the best case is O(b^(d/2)) where b = branching factor and d = depth of the tree, and the base case is when all the preferred nodes are expanded first.