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Momentum-Based Policy Gradient Methods

Authors: Feihu Huang, Shangqian Gao, Pei Jian and Huang Heng

PyTorch Implementation of Momentum-Based Policy Gradient Methods (ICML 2020).

Code uploaded.

Requirements

pytorch 1.1.0
garage 2019.10.1
mujuco
gym
If you do not install mujuco, then only CartPole environment is available.

Usage

To run IS-MBPG

python MBPG_test.py --env CartPole

To run IS-MBPG*

python MBPG_test.py --env CartPole --IS_MBPG_star True

To run HA-MBPG

python MBPG_HA_test.py --env CartPole

To run different environments change --env to one of the followings: "CartPole", "Walker", "Hopper" or "HalfCheetah". If you want to use our algorithms on different enviroment, you need to implement it by yourself, but it should be pretty straightforward.

Citation

@InProceedings{huang2020accelerated,
  author    = {Huang, Feihu and Gao, Shangqian and Pei, Jian and Huang, Heng},
  title     = {Momentum-Based Policy Gradient Methods},
  booktitle = {Proceedings of the 37th International Conference on Machine Learning},
  year      = {2020},}

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