Since the launch of the Deep Reinforcement Learning Course, many students have created amazing projects that you should check out and consider participating in.
If you’ve created an interesting project, don’t hesitate to add it to this list by opening a pull request on the GitHub repository.
The projects are arranged based on the date of publication in this page.
This project is a space game environment with trained neural network for AI.
AI is trained by Reinforcement learning algorithm based on UnityMLAgents and RLlib frameworks.
Play the Game here 👉 https://swingshuffle.itch.io/spacescalvagerai
Check the Unity project here 👉 https://github.com/HighExecutor/SpaceScalvagerAI
In this project, Sookeyy created a low poly racing game and trained a car to drive.
Check out the demo here 👉 https://sookeyy.itch.io/neuralnitro
In this project, Eric Dong recreates Bill Seiler’s 1985 version of Space War in Pygame and uses reinforcement learning (RL) to train AI agents.
This project is currently in development!
Dev/Edge version:
Stable version:
TBA
Check out the source here 👉 https://github.com/e-dong/space-war-rl
Check out his blog here 👉 https://dev.to/edong/space-war-rl-0-series-introduction-25dh
In this project, student has explored training a Decision Transformer for stock trading. In phase-1, offline training has been implemented. He intends to incorporate online fine-tuning in the next version.
Check out the source here 👉 https://github.com/ra9hur/Decision-Transformers-For-Trading
< > Update on GitHub