https://github.com/chendrag/sfbc
Codes accompanying the paper "Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling" (ICLR 2023) https://arxiv.org/abs/2209.14548
https://github.com/chendrag/sfbc
diffusion expressive generative offline reinforcement-learning score-based
Last synced: 11 months ago
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Codes accompanying the paper "Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling" (ICLR 2023) https://arxiv.org/abs/2209.14548
- Host: GitHub
- URL: https://github.com/chendrag/sfbc
- Owner: ChenDRAG
- Created: 2023-02-18T13:50:29.000Z (about 3 years ago)
- Default Branch: master
- Last Pushed: 2023-10-11T09:15:15.000Z (over 2 years ago)
- Last Synced: 2025-03-18T11:11:26.237Z (12 months ago)
- Topics: diffusion, expressive, generative, offline, reinforcement-learning, score-based
- Language: Python
- Homepage:
- Size: 16.7 MB
- Stars: 38
- Watchers: 1
- Forks: 5
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling
This is a pytorch implementation of SfBC: [Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling](https://arxiv.org/abs/2209.14548).
\* **For diffusion-based offline RL, we recommend trying our subsequent work, QGPO([paper](https://arxiv.org/abs/2304.12824); [Github](https://github.com/ChenDRAG/CEP-energy-guided-diffusion)). Compared with SfBC, QGPO has improved computational efficiency and noticeably better performance.**
## Requirements
- See conda requirements in `requirements.yml`
## Quick Start
Train the behavior model:
```shell
$ python3 train_behavior.py
```
Train the critic model and plot evaluation scores with tensorboard:
```shell
$ python3 train_critic.py
```
Evaluation only:
```shell
$ python3 evaluation.py
```
## Citing
If you find this code release useful, please reference in your paper:
```
@inproceedings{
chen2023offline,
title={Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling},
author={Huayu Chen and Cheng Lu and Chengyang Ying and Hang Su and Jun Zhu},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
}
```
## Note
+ Contact us at: chenhuay17@gmail.com if you have any question.