The source code for the paper Guided Exploration in Reinforcement Learning via Monte Carla Critic Optimization Arxiv, presented at
The experiments were run with python3.10 and mujoco 2.3.7, install full env via
pip install -r requirements.txt
Run single training
python train.py --env point_mass-easy --algo MOCCO --device cuda:0 --seed 0
Run on many seeds
For running an algorithm on many many seeds to reproduce paper results, specify needed algorithm as a script file (in /scripts folder) and set needed env as a first argument:
bash scripts/mocco.sh point_mass-easy cuda:0
