43 lines
1.3 KiB
Markdown
43 lines
1.3 KiB
Markdown
# mujoco-maze
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Some maze environments for reinforcement learning(RL) using [mujoco-py] and
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[openai gym][gym].
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Thankfully, this project is based on the code from [rllab] and [tensorflow/models][models].
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## Environments
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- PointUMaze/AntUmaze
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- PointUMaze-v0/AntUMaze-v0 (Distance-based Reward)
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- PointUmaze-v1/AntUMaze-v1 (Goal-based Reward i.e., 1.0 or -ε)
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- Point4Rooms/Ant4Rooms
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- Point4Rooms-v0/Ant4Rooms-v0 (Distance-based Reward)
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- Point4Rooms-v1/Ant4Rooms-v1 (Goal-based Reward)
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- Point4Rooms-v2/Ant4Rooms-v2 (Multiple Goals (0.5 pt or 1.0 pt))
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- PointPush/AntPush
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- PointPush-v0/AntPush-v0 (Distance-based Reward)
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- PointPush-v1/AntPush-v1 (Goal-based Reward)
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- PointFall/AntFall
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- PointFall-v0/AntFall-v0 (Distance-based Reward)
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- PointFall-v1/AntFall-v1 (Goal-based Reward)
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## License
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This project is licensed under Apache License, Version 2.0
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([LICENSE-APACHE](LICENSE) or http://www.apache.org/licenses/LICENSE-2.0).
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[gym]: https://github.com/openai/gym
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[models]: https://github.com/tensorflow/models/tree/master/research/efficient-hrl
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[mujoco-py]: https://github.com/openai/mujoco-py
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[rllab]: https://github.com/rll/rllab
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