The implement of all kinds of dqn reinforcement learning with Pytorch
-
Updated
Mar 25, 2021 - Python
The implement of all kinds of dqn reinforcement learning with Pytorch
Learning to draw samples: with application to amortized maximum likelihood estimator for generative adversarial learning
Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow
Investigating Transfer Learning in Modern Deep Reinforcement Learning Architectures
Implementation of Soft QLearning Algorithm
A codebase for continuous action spaces Reinforcement Learning algorithms
In this piece of work, I have implemented Soft Quality Imitation Learning (SQIL) on Cartpole game environment. Now I'm trying to implement the algorithm on VizDoom Game Environment. It's still in progess.
Add a description, image, and links to the soft-q-learning topic page so that developers can more easily learn about it.
To associate your repository with the soft-q-learning topic, visit your repo's landing page and select "manage topics."