Pong AI Challenge
A downloadable game
In 2023 I started studying AI, machine learning and related areas. I started with tutorials and courses but soon realized I wanted to apply this knowledge to gaming. This led me to create the Pong AI Challenge, my first project built from the ground up, in which I aimed at training an AI agent to play Pong using Reinforcement Learning.
This project was developed in Python. I used Pygame for rendering and event handling, Open AI's Gym and Stable Baselines 3 for training a DQN model in a custom environment, and Optuna for hyperparameter optimization.
The project features three different Game Modes:
- AI vs. Human: Where a human player can compete against the AI agent.
- AI vs Dummy: Watch the AI agent play against a basic deterministic "dummy" AI that only tracks the ball's vertical position (Y position) without any strategic play.
- AI vs AI: Watch two AI agents, trained identically, compete.
I developed this project over the course of 5 weeks, working an average of 2 hours per day on it.
It's important to note that I'm a game designer with an interest in coding, rather than a professional programmer. Therefore, my code might not meet professional standards, and some tasks took longer than they might for an experienced programmer. However, embracing these challenges was also part of my learning journey!
Learn more about this project on my website:
Download
Install instructions
- Simply unzip the file and launch the executable (Pong AI challenge.exe).
- Given the project's size, loading the game may take a few minutes.
The larger file size is due to the inclusion of several Python libraries, ensuring the game is playable even without Python or a development environment installed on the user's machine.
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