Deep RL Course documentation

Student Works

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Student Works

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 youโ€™ve created an interesting project, donโ€™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.

Space Scavanger AI

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.

Space Scavanger AI

Play the Game here ๐Ÿ‘‰ https://swingshuffle.itch.io/spacescalvagerai

Check the Unity project here ๐Ÿ‘‰ https://github.com/HighExecutor/SpaceScalvagerAI

Neural Nitro ๐ŸŽ๏ธ

Neural Nitro

In this project, Sookeyy created a low poly racing game and trained a car to drive.

Check out the demo here ๐Ÿ‘‰ https://sookeyy.itch.io/neuralnitro

Space War ๐Ÿš€

SpaceWar

In this project, Eric Dong recreates Bill Seilerโ€™s 1985 version of Space War in Pygame and uses reinforcement learning (RL) to train AI agents.

This project is currently in development!

Demo

Dev/Edge version:

Stable version:

Community blog posts

TBA

Other links

Check out the source here ๐Ÿ‘‰ https://github.com/e-dong/space-war-rl
Check out his blog here ๐Ÿ‘‰ https://dev.to/edong/space-war-rl-0-series-introduction-25dh

Decision Transformers for Trading

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.

DT for Trading
Source: Stanford CS25: V1 I Decision Transformer: Reinforcement Learning via Sequence Modeling

Check out the source here ๐Ÿ‘‰ https://github.com/ra9hur/Decision-Transformers-For-Trading

< > Update on GitHub