Files
bullet3/examples/pybullet/gym/train_pybullet_cartpole.py
Erwin Coumans 21f9d1b816 refactor pybullet/gym to allow instantiating environments directly from a pybullet install:
work-in-progress (need to add missing data files, fix paths etc)

example:

pip install pybullet
pip install gym

python
import gym
import pybullet
import pybullet_envs
env = gym.make("HumanoidBulletEnv-v0")
2017-08-22 00:42:02 -07:00

34 lines
755 B
Python

import gym
from pybullet_envs.bullet.cartpole_bullet import CartPoleBulletEnv
from baselines import deepq
def callback(lcl, glb):
# stop training if reward exceeds 199
is_solved = lcl['t'] > 100 and sum(lcl['episode_rewards'][-101:-1]) / 100 >= 199
return is_solved
def main():
env = CartPoleBulletEnv(renders=False)
model = deepq.models.mlp([64])
act = deepq.learn(
env,
q_func=model,
lr=1e-3,
max_timesteps=100000,
buffer_size=50000,
exploration_fraction=0.1,
exploration_final_eps=0.02,
print_freq=10,
callback=callback
)
print("Saving model to cartpole_model.pkl")
act.save("cartpole_model.pkl")
if __name__ == '__main__':
main()