
This repository is the implementation of the paper **Demonstration-Guided Multi-Objective Reinforcement Learning**.
You can use DGMORL.py to run the experiment of DST and Minecart. 
You can use DGMORL_contiuous.py to run the experiment of MO-Hopper, MO-Ant and MO-Humanoid. 

use

conda env create -f DGMORL.yml

to import the environment to run the script.

The implementation is adapted from https://github.com/LucasAlegre/morl-baselines
Alegre, Lucas N., et al. "Sample-efficient multi-objective learning via generalized policy improvement prioritization." arXiv preprint arXiv:2301.07784 (2023).

Also please refer to the GPI-LS and GPI-PD via https://github.com/LucasAlegre/morl-baselines