Minimax Algorithm for Tic-Tac-Toe
RL Environments, Games & Applications DS practice problem on Onlearn.
Difficulty: medium.
Topics: Minimax Algorithm for Tic-Tac-Toe, Alpha-Beta Pruning, Zero-Sum Games, Depth-First Traversal, Terminal State Detection, Minimax Backtracking, Game Theory, Search Algorithms, Artificial Intelligence, Decision Theory, Discrete Mathematics, Adversarial Search, Recursive Problem Solving, State Space Representation, Heuristic Evaluation, Combinatorial Optimization.
Implement the Minimax algorithm to choose the best move for a Tic Tac Toe AI player. Given a Tic Tac Toe board and a player (either 'X' or 'O'), write a function that returns the optimal next move as a tuple (row, col). Your function should assume both players play optimally and return a move that maximizes the AI's chance of winning (or minimizes the chance of losing if no win is possible). The board is given as a 3x3 NumPy array with entries 'X', 'O', or '', and the player to move is a string ('X' or 'O'). Do not use any external game libraries.