AI_Connect4_game is an implementation of the classic Connect 4 game in Python, featuring an artificial intelligence opponent that employs the Minimax search algorithm with Alpha-Beta pruning. In this strategic game, players take turns dropping colored discs into a vertically suspended grid, aiming to connect four of their own discs horizontally, vertically, or diagonally before the opponent does.

The Minimax algorithm is a decision-making algorithm widely used in two-player games, such as Connect 4, where the objective is to maximize the score when the AI is playing and minimize the score when the opponent is playing. It explores all possible moves in a game tree, assigning scores to each move and selecting the move with the highest score for the AI player.

Alpha-Beta pruning is an enhancement to the Minimax algorithm, designed to reduce the number of nodes evaluated in the search tree. This optimization minimizes the time complexity of the algorithm by eliminating branches that are guaranteed not to influence the final decision. The algorithm maintains two values, alpha and beta, representing the minimum score the maximizing player is assured of and the maximum score the minimizing player is assured of, respectively. If a node's score is found to be outside the alpha-beta window, the search algorithm prunes that branch, saving computational resources.

The combination of Minimax and Alpha-Beta pruning in AI_Connect4_game results in a formidable opponent capable of making intelligent and efficient decisions, enabling it to often emerge victorious against human players. This implementation showcases the power of these algorithms in creating strategic and competitive artificial intelligence for gaming environments.