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Simple maze environments using mujoco-py

Project description

mujoco-maze

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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

    • PointUMaze-v0/AntUMaze-v0 (Distance-based Reward)
    • PointUmaze-v1/AntUMaze-v1 (Goal-based Reward i.e., 1.0 or -ε)
  • Point4Rooms/Ant4Rooms

    Point4Rooms

    • 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

    • PointPush-v0/AntPush-v0 (Distance-based Reward)
    • PointPush-v1/AntPush-v1 (Goal-based Reward)
  • PointFall/AntFall

    PointFall

    • PointFall-v0/AntFall-v0 (Distance-based Reward)
    • PointFall-v1/AntFall-v1 (Goal-based Reward)
  • PointBilliard

    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).

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