Hierarchical Reinforcement envs in pybullet
This package was created because all of the HRL locomotion envs are only available in mujoco. This is an implementation of as many as possible in pybullet.
Install
pip install pybullet hrl_pybullet_envs
This project requires pybullet-gym which must be installed along side this package.
Envs:
- AntGatherBulletEnv-v0
- AntMazeBulletEnv-v0
- AntMjBulletEnv-0
- AntFlagrunBulletEnv-v0
- PointGatherBulletEnv-v0
Example
Also see this notebook
import hrl_pybullet_envs
import gym
import numpy as np
env = gym.make('AntGatherBulletEnv-v0')
env.render()
ob = env.reset()
tot_rew = 0
for i in range(1000):
# Take random actions
ob, rew, done, _ = env.step(np.random.uniform(-1, 1, env.action_space.shape))
tot_rew += rew
if done: break
print(f'Achieved total reward of: {tot_rew}')
1 maintainer
Release files for hrl-pybullet-envs 0.2.37
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| hrl_pybullet_envs-0.2.37-py3-none-any.whl | Python 3 | none | any | Details |
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Release files / hrl_pybullet_envs-0.2.37.tar.gz
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