Reinforcement learning for cat walking motion through Unity ML-Agents Toolkit

• Installation page: https://github.com/Unity-Technologies/ml-agents/blob/release_10_docs/docs/Installation.md
• Starting guide: https://github.com/Unity-Technologies/ml-agents/blob/release_10_docs/docs/Getting-Started.md

Or follow these instructions

1. Get python 3.8: https://www.python.org/downloads/release/python-3810/

2. Go to project folder

3. py -3.8 -m venv venv venv\Scripts\activate pip3 install torch==1.7.0 -f https://download.pytorch.org/whl/torch_stable.html pip3 install mlagents

4. For [Pillow, grpcio, h5py], do: pip3 uninstall [package] pip3 install [package] --upgrade

5. pip3 install protobuf==3.20.* pip3 install numpy==1.21.2

6. Try: mlagents-learn --help -this should display a help screen properly

7. Clone this repository

8. In Unity Hub, select open project from disk and open the cloned CatWalk folder

9. Go to 'Prefab' and select 'cat_stand'

10. Go to 'TFModels' and drag the approprate .onnx model file into the Model parameter of the cat_stand. It should be under 'Behavioral Parameters'

11. Now just press play and the model will do what it was trained

• Use command mlagents-learn CatWalk/config/CatWalk.yaml --run-id=catWalk then press play in Unity

• Use command tensorboard --logdir results to observe training progress

First, must create executable by building project, and adding to a folder (like CatWalk_Build3), then access executable using that folder like as shown below

• Run multi env no graphics mlagents-learn CatWalk/config/CatWalk.yaml --run-id=catWalk_stand_3 --env=Builds/CatWalk_Build_StandOnly_3 --num-envs=8 --torch-device cuda --no-graphics --resume

• Display 1 window mlagents-learn CatWalk/config/CatWalk.yaml --run-id=catWalk_stand_3 --env=Builds/CatWalk_Build_StandOnly_3 --num-envs=1 --torch-device cuda --width 1200 --height 800 --resume