The goal is to train the agents 'Ant-v3' and Humanoid-v3' from the MuJoCo environments of OpenAI Gym to move on the circumference of a circle centered on the origin while remaining within a safety region smaller than the radius of the circle.
The Environments were inspired by the circle environments in https://arxiv.org/pdf/1705.10528.pdf and are directly modified from the implementations in OpenAI Gym.
Go to environment directory
cd mujoco-circle
then install by
pip install -e .
After installation is complete, you can create an instance
of the environment with gym.make('mujoco_circle:AntCircle-v0')
(For HumanoidCircle, replace 'AntCircle-v0' with
'HumanoidCircle-v0').
The code snippet below generates an episode of maximum length 1000 using a random policy from the AntCircle environment.
import gym
env = gym.make('mujoco_circle:AntCircle-v0')
state = env.reset()
for _ in range(1000):
action = env.action_space.sample()
next_state, reward, done, info = env.step(action)
if done:
break
env.close()