This repository contains implementation of the preference-based multi-objective reinforcement learning (PBMORL).
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|--morl --> source codes for PBMORL
|--configs --> configs of environments
|--environments --> available environments of PBMORL
|--externals --> external algorithm package of PPO(https://github.com/ikostrikov/pytorch-a2c-ppo-acktr-gail).
- Python version: tested in Python 3.7.4
- Torch version: tested in Torch 1.10.2
- MuJoCo : install mujoco and mujoco-py by following the instructions in mujoco-py.
You can either install the dependencies in a conda virtual env (recomended) or manually.
For conda virtual env installation, create a virtual env named pbmorl by:
conda env create -f PBMORL_environment.yml
conda activate pbmorl
cd morl
python run.py
The obtained policies are stored under the folders of morl/env_name/final