PyTorch implementation of the implicit Q-learning algorithm (IQL)

Related tags

Deep Learning reinforcement-learning q-learning iql offline-rl implicit-q-learning batch-rl
Overview

Implicit-Q-Learning (IQL)

PyTorch implementation of the implicit Q-learning algorithm IQL (Paper)

Currently only implemented for online learning. Offline RL version with D4RL will be updated soon.

Run

python train.py

Results

Pendulum

alt-text

Reference

Original JAX implementation: IQL

Help and issues:

Im open for feedback, found bugs, improvements or anything. Just leave me a message or contact me.

Author

  • Sebastian Dittert

Feel free to use this code for your own projects or research.

@misc{IQL,
  author = {Dittert, Sebastian},
  title = {PyTorch Implementation of Implicit-Q-Learning (IQL)},
  year = {2021},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/BY571/Implicit-Q-Learning}},
}
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Comments
  • offline training

    offline training

    Hi! Is offline training now fully supported? I am confused because I see the train_offline script but in the README I see that you say that offline training is not implemented. Maybe not with the D4RL dataset, but should it work for any dataset of experiences (s,a,r,s',d)?

    Thank you!

    opened by roger-creus 0
  • Question for runtime

    Question for runtime

    Hi, Thanks for sharing the implementation code.

    I have a question about IQL experimental runtime on PyTorch. Actually, I tried to re-implement it with tensorflow-keras. But the runtime is quite slow. (on HalfCheetah-medium-v2 with GTX 1080TI)

    If you don't mind, could you share the the overall runtime on that environment or computing resource you use? Thanks in advance.

    opened by goodboychan 0
  • bad result on Antmaze enviornment

    bad result on Antmaze enviornment

    It works well on mujoco environments, but not on antmze environment .It did not work even if I changed the parameters according to the paper(expectile=0.9, temperature=10). Can you help me please?

    opened by dljzx 1
  • scalar observation

    scalar observation

    Sebastian, thank you for this great code. I am trying to run some examples here (starting from offline training of antmaz) however I receive an error about "assert np.isscalar(low) and np.isscalar(high)" from the BOX space which is returned from line 18th of single_precision.py". is there something I may missed ? thank you

    opened by amirmirzaeinia 0
Owner
Sebastian Dittert
Mechanical Engineer M.Sc. Interested in Deep Reinforcement Learning, AI and Robotics/Self-driving cars
Sebastian Dittert
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