Q-Learning for Games: Teaching an Agent Tic-Tac-Toe Through Self-Play

Tic-tac-toe is a solved game. Any competent adult can force a draw every time. But can an agent figure that out with zero human knowledge? Give two agents a blank board, a few simple rules about wins and losses, and nothing else. No opening theory, no strategy guides, no human games to study. After 100,000 games of fumbling against each other, they discover forks, blocking, and centre-first openings entirely on their own. This is Q-learning applied to games. In our previous Q-learning post , the