https://github.com/sweetice/mepe
Official implementation of MEPE
https://github.com/sweetice/mepe
Last synced: 7 months ago
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Official implementation of MEPE
- Host: GitHub
- URL: https://github.com/sweetice/mepe
- Owner: sweetice
- Created: 2022-10-27T11:59:44.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2022-10-28T13:14:58.000Z (almost 3 years ago)
- Last Synced: 2025-01-20T10:11:42.519Z (9 months ago)
- Language: Python
- Size: 23.4 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Code for paper: A Minimalist Ensemble Policy Evaluation Operator for Deep Reinforcement Learning
## Install
### Optionally: Create a new python virtual environment
We recommend readers use the anaconda tool.
```shell
conda create -n mepe python=3.7.4
```
And then activate the created environment
```shell
conda activate mepe
```
###
Firstly, install the requirements.txt
```shell
pip install -r requirements.txt
```
The required python package is as follows:
```shell
torch==1.7.1+cu101
numpy==1.18.1
gym==0.12.1
pybullet==2.7.1
roboschool==1.0.48
pandas==1.0.1
tqdm
scikit-image
tensorboard
torch
torchvision
gym==0.25.1
patchelf
termcolor
seaborn==0.9.0
opencv-python
kornia
```
## Run
For running ME-DDPG:
```shell
cd Bullet
python main_me_ddpg.py --env HopperBulletEnv-v0 --seed 0 --dropout_p 0.1
```
```bash
(mepe) python main_me_ddpg.py --env HopperBulletEnv-v0 --seed 0 --dropout_p 0.1
---------------------------------------
Policy: ME-DDPG, Env: HopperBulletEnv-v0, Seed: 0
---------------------------------------
3%|██▍ | 28308/1000000 [00:28<59:30, 272.17it/s]
```
For running ME-SAC:
```shell
cd Bullet
python main_me_sac.py --env HopperBulletEnv-v0 --seed 0 --dropout_p 0.1
```
```bash
(mepe) python main_me_sac.py --env HopperBulletEnv-v0 --seed 0 --dropout_p 0.1
---------------------------------------
Policy: ME-SAC, Env: HopperBulletEnv-v0, Seed: 0
---------------------------------------
3%|██▌ | 30202/1000000 [00:47<1:36:08, 168.12it/s]
```
For running ME-CURL
```shell
cd Atari
python main.py --game=ms_pacman
```
```shell
(mepe) python main.py --game=ms_pacman
Algorithm name: mepe
2%|█▍ | 1703/100000 [00:11<1:22:28, 19.86it/s]
```