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Model-based Offline Policy Optimization with Adversarial Network

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Overview

This is an official implementation of the offline model-based RL algorithm MOAN all by pytorch.

Dependencies

  • MuJoCo 2.0
  • Gym 0.22.0
  • D4RL
  • PyTorch 1.8+

Usage

Train

# for hopper-medium-replay-v2 task
python3 train.py --task "hopper-medium-replay-v2" --rollout-length 5 --seed 50 --d-coeff 0.1
# for halfcheetah-medium-replay-v2 task
python3 train.py --task "hopper-medium-replay-v2" --rollout-length 5 --seed 50 --d-coeff 0.1
# for walker2d-medium-replay-v2 task
python3 train.py --task "hopper-medium-replay-v2" --rollout-length 5 --seed 50 --d-coeff 0.1

Reference

If you find this code useful, please reference in our paper:

@article{yang2023model,
  title={Model-based offline policy optimization with adversarial network},
  author={Yang, Junming and Chen, Xingguo and Wang, Shengyuan and Zhang, Bolei},
  journal={arXiv preprint arXiv:2309.02157},
  year={2023}
}

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