Implement Alpha-beta pruning of Minimax Search Algorithm for a Simple TIC-TAC-TOE game

The project involves developing a Tic-Tac-Toe game implementation incorporating the Alpha-Beta pruning with the Minimax algorithm. Using this algorithm, the computer player analyzes the game state, evaluates possible moves, and selects the optimal action based on the anticipated outcomes.

recursively evaluates all possible moves and their potential outcomes, creating a game tree.

Alpha–Beta (𝛼−𝛽) algorithm is actually an improved minimax using a heuristic. It stops evaluating a move when it makes sure that it’s worse than a previously examined move. Such moves need not to be evaluated further.

When added to a simple minimax algorithm, it gives the same output but cuts off certain branches that can’t possibly affect the final decision — dramatically improving the performance