generalized-advantage-estimation
Here are 8 public repositories matching this topic...
Language:All
Tutorials for reinforcement learning in PyTorch and Gym by implementing a few of the popular algorithms. [IN PROGRESS]
- Updated
Oct 23, 2020 - Jupyter Notebook
Proximal Policy Optimization(PPO) with Intrinsic Curiosity Module(ICM)
- Updated
Jan 12, 2019 - Python
A collection of Reinforcement Learning implementations with PyTorch
- Updated
Mar 22, 2022 - Python
Phasic-Policy-Gradient
- Updated
Dec 1, 2020 - Python
An implementation from the state-of-the-art family of reinforcement learning algorithms Proximal Policy Optimization using normalized Generalized Advantage Estimation and optional batch mode training. The loss function incorporates an entropy bonus.
- Updated
Dec 26, 2022 - Python
Recurrent Policies for Handling Partially Observable Environments
- Updated
Aug 29, 2022 - Jupyter Notebook
Example TRPO implementation with ReLAx
- Updated
Aug 29, 2022 - Jupyter Notebook
Example PPO implementation with ReLAx
- Updated
Aug 29, 2022 - Jupyter Notebook
Improve this page
Add a description, image, and links to thegeneralized-advantage-estimation topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with thegeneralized-advantage-estimation topic, visit your repo's landing page and select "manage topics."