Files
bullet3/examples/pybullet/gym/train_pybullet_zed_racecar.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

42 lines
921 B
Python

import gym
from pybullet_envs.bullet.racecarZEDGymEnv import RacecarZEDGymEnv
from baselines import deepq
import datetime
def callback(lcl, glb):
# stop training if reward exceeds 199
total = sum(lcl['episode_rewards'][-101:-1]) / 100
totalt = lcl['t']
is_solved = totalt > 2000 and total >= -50
return is_solved
def main():
env = RacecarZEDGymEnv(renders=False)
model = deepq.models.cnn_to_mlp(
convs=[(32, 8, 4), (64, 4, 2), (64, 3, 1)],
hiddens=[256],
dueling=False
)
act = deepq.learn(
env,
q_func=model,
lr=1e-3,
max_timesteps=10000,
buffer_size=50000,
exploration_fraction=0.1,
exploration_final_eps=0.02,
print_freq=10,
callback=callback
)
print("Saving model to racecar_zed_model.pkl")
act.save("racecar_zed_model.pkl")
if __name__ == '__main__':
main()