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

Last update: Dec 30, 2022

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

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}},
}

Owner

Sebastian Dittert

Mechanical Engineer M.Sc. Interested in Deep Reinforcement Learning, AI and Robotics/Self-driving cars

GitHub Repository

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

Related tags

Overview

Implicit-Q-Learning (IQL)

Run

Results

Pendulum

Reference

Help and issues:

Author

Owner

Sebastian Dittert

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

Related tags

Overview

Implicit-Q-Learning (IQL)

Run

Results

Pendulum

Reference

Help and issues:

Author

Owner

Sebastian Dittert

The trained model and denoising example for paper : Cardiopulmonary Auscultation Enhancement with a Two-Stage Noise Cancellation Approach

Elegy is a framework-agnostic Trainer interface for the Jax ecosystem.

Deep Q-network learning to play flappybird.

Garbage Detection system which will detect objects based on whether it is plastic waste or plastics or just garbage.

Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"

Mixed Neural Likelihood Estimation for models of decision-making

DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks

The official PyTorch implementation of the paper: *Xili Dai, Xiaojun Yuan, Haigang Gong, Yi Ma. "Fully Convolutional Line Parsing." *.

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This is the official implementation code repository of Underwater Light Field Retention : Neural Rendering for Underwater Imaging (Accepted by CVPR Workshop2022 NTIRE)

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