: In most implementations, the AI will prioritize the center square if it's open, as it offers the most strategic paths for horizontal, vertical, and diagonal wins. 3. Building the Engine
) is the number of future steps the agent looks ahead to maximize its reward. iohorizontictactoeaix
function checkWin(board, player) for (let row = 0; row < 3; row++) if (board[row][0] === player && board[row][1] === player && board[row][2] === player) return true; : In most implementations, the AI will prioritize
# 2. Maximizing Player (AI) if is_maximizing: best_score = -infinity for each empty spot on board: make_move(AI) score = minimax(board, depth + 1, false) undo_move() best_score = max(score, best_score) return best_score function checkWin(board, player) for (let row = 0;
Tic-Tac-Toe is a "solved game," meaning that with perfect play from both sides, every match will end in a draw. For a computer to achieve this level of perfection, it doesn't just play randomly; it uses a mathematical strategy to evaluate every possible outcome. 1. The Brain: The Minimax Algorithm The most common engine behind a Tic-Tac-Toe AI is the Minimax Algorithm
: Experimental versions of AIXI have successfully learned to play and win at Tic-Tac-Toe and other games like Othello without being programmed with the rules. 🔍 Breakdown of the Term