Simple maze environments using mujoco-py
Project description
mujoco-maze
Some maze environments for reinforcement learning(RL) using mujoco-py and openai gym.
Thankfully, this project is based on the code from rllab and tensorflow/models.
Environments
-
PointUMaze/AntUmaze
- PointUMaze-v0/AntUMaze-v0 (Distance-based Reward)
- PointUmaze-v1/AntUMaze-v1 (Goal-based Reward i.e., 1.0 or -ε)
-
Point4Rooms/Ant4Rooms
- Point4Rooms-v0/Ant4Rooms-v0 (Distance-based Reward)
- Point4Rooms-v1/Ant4Rooms-v1 (Goal-based Reward)
- Point4Rooms-v2/Ant4Rooms-v2 (Multiple Goals (0.5 pt or 1.0 pt))
-
PointPush/AntPush
- PointPush-v0/AntPush-v0 (Distance-based Reward)
- PointPush-v1/AntPush-v1 (Goal-based Reward)
-
PointFall/AntFall
- PointFall-v0/AntFall-v0 (Distance-based Reward)
- PointFall-v1/AntFall-v1 (Goal-based Reward)
-
PointBilliard
- PointBilliard-v0 (Distance-based Reward)
- PointBilliard-v1 (Goal-based Reward)
- PointBilliard-v2 (Multiple Goals (0.5 pt or 1.0 pt))
Warning
This project has some other environments (e.g., reacher and swimmer) but if they are not on README, they are work in progress and not tested well.
License
This project is licensed under Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0).
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
mujoco-maze-0.1.1.tar.gz
(20.0 kB
view hashes)
Built Distribution
Close
Hashes for mujoco_maze-0.1.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 178f9984f2f96d1bd621243b6d20a83a1b92abc3f59e3212bcc849b47c8f5422 |
|
MD5 | ad0cdb5cf405d9641e87420e0964252b |
|
BLAKE2b-256 | 2463d7cf04b2ae636a93c4e9b20aff0f5141bb744351513a8fd1a00d6b51d479 |