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Alpha–Beta Pruning Implementation for Optimal Decision-Making

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Alpha-Beta Pruning

Alpha–Beta Pruning Implementation for Optimal Decision-Making


Overview

The alpha-beta pruning algorithm is an optimization technique for the minimax algorithm, which is commonly used in game-playing AI. The minimax algorithm evaluates all possible moves for a player, and then their opponent's response to those moves, and so on, to determine the best move for the original player. The alpha-beta pruning algorithm is used to speed up this process by eliminating branches of the game tree that are not likely to affect the final outcome. In this project, the alpha-beta pruning algorithm is being tested on the single-player mode of a Tic-Tac-Toe game.


Getting Started

1. Fork the project and clone the repository:

* git clone git://github.com/ak811/alpha-beta-pruning.git

2. Import the project via Android Studio:

* File -> Open -> Jaga root build.gradle
* Import the project
* Wait until everything is synced and indexed
* Make sure the Gradle sync succeeds

3. You're ready to go!

* The documentation will be provided soon.

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