CS_ALearn/deep-rl-class
1
0
Fork 0
mirror of https://github.com/huggingface/deep-rl-class.git synced 2026-04-03 18:47:48 +08:00
Code Issues Projects Releases Wiki Activity

Update readme links

Browse Source
This commit is contained in:
Thomas Simonini
2022-05-30 16:04:29 +02:00
committed by GitHub
parent 77abdfe1e1
commit 9664ef096b
1 changed files with 2 additions and 2 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
README.md
View File

@@ -23,8 +23,8 @@ This course is **self-paced** you can start when you want 🥳.
| 📆 Publishing date | 📘 Unit | 👩‍💻 Hands-on |
|---------------|----------------------------------------------------------|----------------------------------------------------------------------------------------------------------|
| [Published 🥳](https://github.com/huggingface/deep-rl-class/tree/main/unit1#unit-1-introduction-to-deep-reinforcement-learning) | [An Introduction to Deep Reinforcement Learning](https://github.com/huggingface/deep-rl-class/tree/main/unit1) | [Train a Deep Reinforcement Learning lander agent to land correctly on the Moon 🌕 using Stable-Baselines3](https://github.com/huggingface/deep-rl-class/blob/main/unit1/unit1.ipynb) |
| May, the 11th | [Bonus](https://discord.com/channels/879548962464493619/968114737655214080/973937495546925056) | |
| May, the 18th/May, the 20th | [Q-Learning](https://github.com/huggingface/deep-rl-class/blob/main/unit2/README.md) | Train an agent to cross a Frozen lake in this new version of the environment. |
| [Published 🥳](https://github.com/huggingface/deep-rl-class/tree/main/unit1/unit1-bonus) | [Bonus](https://github.com/huggingface/deep-rl-class/tree/main/unit1/unit1-bonus) | |
| [Published 🥳](https://github.com/huggingface/deep-rl-class/blob/main/unit2/README.md)| [Q-Learning](https://github.com/huggingface/deep-rl-class/blob/main/unit2/README.md) | [Train an agent to cross a Frozen lake ⛄ and train an autonomous taxi 🚖](https://github.com/huggingface/deep-rl-class/blob/main/unit2/unit2.ipynb). |
| June, the 1st | Deep Q-Learning and improvements | Train a Deep Q-Learning agent to play Space Invaders |
| | Policy-based methods | 🏗️ |
| | Actor-Critic Methods | 🏗️ |