Custom environment for OpenAI gym
Project description
gym-trajectory
Custom environment for OpenAI gym
N-dimensional trajectory
import gym
import gym_trajectory
env = gym.make('Trajectory-v0')
observation = env.reset()
while True:
(observation, reward, done, info) = env.step(env.action_space.sample())
env.render()
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
gym-trajectory-0.1.tar.gz
(3.9 kB
view hashes)
Built Distribution
Close
Hashes for gym_trajectory-0.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | a5abed279a932624f37d6850053b31fa25fe1677027456f1ac53cd48a429ccb4 |
|
MD5 | 83e64cdbedc10779ad822ad5327c0397 |
|
BLAKE2b-256 | d11f71e64bd186c077bac9b2b569e429a9a4f15128dfb8a4915f8403943f8a20 |