Deep RL Course documentation

Student Works

Deep RL Course

Unit 0. Welcome to the course

Unit 1. Introduction to Deep Reinforcement Learning

Bonus Unit 1. Introduction to Deep Reinforcement Learning with Huggy

Live 1. How the course work, Q&A, and playing with Huggy

Unit 2. Introduction to Q-Learning

Unit 3. Deep Q-Learning with Atari Games

Bonus Unit 2. Automatic Hyperparameter Tuning with Optuna

Unit 4. Policy Gradient with PyTorch

Unit 5. Introduction to Unity ML-Agents

Unit 6. Actor Critic methods with Robotics environments

Unit 7. Introduction to Multi-Agents and AI vs AI

Unit 8. Part 1 Proximal Policy Optimization (PPO)

Unit 8. Part 2 Proximal Policy Optimization (PPO) with Doom

Bonus Unit 3. Advanced Topics in Reinforcement Learning

Introduction Model-Based Reinforcement Learning Offline vs. Online Reinforcement Learning Generalisation Reinforcement Learning Reinforcement Learning from Human Feedback Decision Transformers and Offline RL Language models in RL (Automatic) Curriculum Learning for RL Interesting environments to try An introduction to Unreal Learning Agents An Introduction to Godot RL Students projects Brief introduction to RL documentation

Certification and congratulations

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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 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.

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 👉 https://swingshuffle.itch.io/spacescalvagerai

Check the Unity project here 👉 https://github.com/HighExecutor/SpaceScalvagerAI

Neural Nitro 🏎️

Neural Nitro

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

Space War 🚀

SpaceWar

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!

Demo

Dev/Edge version:

https://e-dong.itch.io/spacewar-dev

Stable version:

Community blog posts

TBA

Other links

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

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