Command for training on continual reacher environment:
python train.py --exp=reacher_mppi --plan_steps=20 --num_plan_steps=80
--datasource=continual_reacher --noise_sim=80 --mppi --g_coeff=1.0 --a_coeff=0.01 --v_coeff=0.1 --save_interval=300
--num_env=8
Command for evaluating on continual reacher environment:
python train.py --exp=<exp_name> --plan_steps=20 --num_plan_steps=80 --datasource=continual_reacher
--noise_sim=80 --mppi --g_coeff=10.0 --a_coeff=0.01 --v_coeff=0.1 --save_interval=300 --num_env=1
--resume_iter=<train iteration> --n_benchmark_exp=1 --rl_train=False --train=False
Bibtex for paper:
@article{Du2019ModelBP,
title={Model Based Planning with Energy Based Models},
author={Yilun Du and Toru Lin and Igor Mordatch},
journal={CORL},
year={2019}
}
