https://github.com/d-kicinski/deep-reinforcement-learning

Implementations of deep RL algorithms based on Berkeleys CS294
https://github.com/d-kicinski/deep-reinforcement-learning

python pytorch reinforcement-learning tensorflow

Last synced: 2 months ago
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Implementations of deep RL algorithms based on Berkeleys CS294

• Host: GitHub
• URL: https://github.com/d-kicinski/deep-reinforcement-learning
• Owner: d-kicinski
• Created: 2018-05-03T16:53:52.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2022-12-08T02:12:31.000Z (over 3 years ago)
• Last Synced: 2025-04-09T12:25:26.030Z (about 1 year ago)
• Topics: python, pytorch, reinforcement-learning, tensorflow
• Language: Python
• Homepage:
• Size: 10.5 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 6
• Metadata Files:
  • Readme: README.md

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README

          
# Deep reinforcement algorithms

Implementations of classic Deep RL algorithms, mostly based on CS 294: Deep

Reinforcement Learning at [Berekley](http://rail.eecs.berkeley.edu/deeprlcourse-fa17/index.html)

Current state:

- [X] Policy Gradient:

      Basically my solution to heavily refactored CS294 second homework. Tensorflow ლ(ಠ益ಠლ)

- [ ] DQN

      Still based on CS294 but implemented in  PyTorch ✧ﾟ･: *ヽ(◕ヮ◕ヽ)

   + [X] Discrete action space

   + [ ] Continous action space

## Solved classic control environments: