A2C Baseline | Meta-Gradient Reinforcement Learning | Bootstrapped Meta-Learning |
---|---|---|
$ python main.py --algo A2C --seed 0 --epsilon-EN 3e-1 --lr 1e-1 --gamma 0.99 --log-dir "logs" --max-steps 6400000
Both SGD and Adam are supported, however, it is not encouraged to use Adam otherwise you won't see desired result.
$ python main.py --algo MGRL --seed 0 --lr 1e-1 --meta-lr 1e-4 -epsilon-meta 0.12 --gamma 0.99 --T 15 --max-steps 6400000
$ python main.py --algo BMG -seed 0 --lr 1e-1 --meta-lr 1e-4 --gamma 0.99 --K 7 --L 9 --max-steps 6400000
We use 7 and 9 corresponding to K and L for default, for details, you can redirect to the original paper Bootstrapped Meta-Learning
python plot.py --algo BMG
The results will be stored in results
folder by default. To plot, please specify algorithm name that corresponds to the latest run.
$ pip install -r requirements.txt