The term ends with and "X" .
Together, they suggest : an evolution of the simple game into an extensible framework. It implies a modular AI that can be plugged into various environments, playing not just for a draw, but to optimize for variables (efficiency, speed, or psychological manipulation of an opponent). iohorizontictactoeaix
: Using the Minimax algorithm with Alpha-Beta pruning, an AI can be "unbeatable" in Tic-Tac-Toe, always forcing at least a draw. The term ends with and "X"
def minimax(board, depth, is_maximizing): # 1. Check for terminal state (Win/Loss/Draw) result = check_winner(board) if result == AI: return 10 if result == HUMAN: return -10 if result == DRAW: return 0 : Using the Minimax algorithm with Alpha-Beta pruning,
Recommended for: First-time AI programmers, Tic-Tac-Toe enthusiasts, or those curious about “horizon” in game AI. Not for: Players seeking challenge variation or multiplayer.