Advanced XO Game - Reinforcement Learning Use Case

I made this game in 2018. Took me over 12 hours to do it. But it was fun. It was my first experience with PyGame so took me a bit to understand how it worked.

  • Goal of the game is to put three of your pieces on the board to form a line

  • White and Black take turns. Whoever forms a line first wins.

  • There are 24 available spots and 18 possible winning lines

  • Game is not timed, although I'm outputting it.

  • You can play against the computer

  • Colors are randomly assigned to the player and computer at the beginning of each round

  • Utilized reinforcement learning to train the computer

  • Ran training for around 20 mins which captured around 2% of possible board variations

  • Game will always play best moves when there are obvious winning or loosing scenarios

  • Code available here: https://github.com/manimarashi/projects/tree/main/AdvancedXO

Chess Engine with Python and Pygame

This is a fully functioning chess game written in Python. I used Pygame for the front end.

Took me around 10 hrs to fully write the actual game. I'll try to find some time to develop the AI. I will mainly use MinMaxing and AlphaBeta pruning to develop the AI. I'll also use book openings to make it a bit smarter.

The main challenges will be to optimize the code to help it make decisions in seconds.

I'll share more findings once I develop that part.

you can check out the code here: https://github.com/manimarashi/projects/tree/main/chess