Utilizing reinforcement studying from scratch to show a pc to play Tic-Tac-Toe

It seems that everybody within the AI sector is presently honing their Reinforcement Studying (RL) abilities, particularly in Q-learning, following the current rumours about OpenAI’s new AI mannequin, Q* and I’m becoming a member of in too. Nevertheless, fairly than speculating about Q* or revisiting previous papers and examples for Q-learning, I’ve determined to make use of my enthusiasm for board video games to present an introduction to Q-learning 🤓

On this weblog publish, I’ll create a easy programme from scratch to show a mannequin easy methods to play Tic-Tac-Toe (TTT). I’ll chorus from utilizing any RL libraries like Health club or Steady Baselines; every part is hand-coded in native Python, and the script is merely 100 strains lengthy. When you’re interested by easy methods to instruct an AI to play video games, maintain studying.

You’ll find all of the code on GitHub at https://github.com/marshmellow77/tictactoe-q.

Educating an AI to play Tic-Tac-Toe (TTT) may not appear all that vital. Nevertheless, it does present a (hopefully) clear and comprehensible introduction to Q-learning and RL, which is likely to be vital within the subject of Generative AI (GenAI) since there was hypothesis that stand-alone GenAI fashions, akin to GPT-4, are inadequate for vital developments. They’re restricted by the truth that they’ll solely ever predict the following token and never with the ability to motive in any respect. RL is believed to have the ability to deal with this concern and doubtlessly improve the responses from GenAI fashions.

However whether or not you’re aiming to brush up in your RL abilities in anticipation of those developments, otherwise you’re merely searching for a fascinating introduction to Q-learning, this tutorial is designed for each situations 🤗

At its core, Q-learning is an algorithm that learns the worth of an motion in a selected state, after which makes use of this info to search out the perfect motion. Let’s contemplate the instance of the Frozen Lake recreation, a well-liked single-player recreation used to reveal Q-learning.