README.md

unity_rllib_example

Reinforcement learning example using rllib and unity ml agent

Installation

1. Follow ml-agents installation guide to install ml-agents.

   In step of Install the mlagents Python package

   do Advanced: Local Installation for Development

   conda create -n ml-agents python=3.10.12
   conda activate ml-agents
   conda install -c conda-forge onnx=1.12.0 swig=4.0.2
   cd ml-agents
   pip install torch -f https://download.pytorch.org/whl/torch_stable.html
   pip install -e ./ml-agents-envs
   pip install -e ./ml-agents

2. Follow rllib installation guide to install rllib.

   Follow Building Ray (Python Only)

   # For example, for Python 3.10, MacOS M1:
   pip install -U "ray[all] @https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp310-cp310-macosx_11_0_arm64.whl" protobuf==3.19.6
   pip install "gymnasium[all]"
   
   # This replaces `<package path>/site-packages/ray/<package>`
   # with your local `ray/python/ray/<package>`.
   cd ray
   python python/ray/setup-dev.py -y --skip _private dashboard

3. Open ml-agents/Project with Unity

   You should use the specific version of Unity of project

   In the Unity Hub, go to Projects and add the project located within the zipped folder (click “ADD” in the Unity Hub Projects tab, then navigate to [unzipped folder]/Project and click “Open”)

4. Follow RLlib guide

   python src/unity3d_env_local.py --env 3DBall --framework=torch
   
   # or execute the file
   python src/unity3d_env_local.py --env 3DBall --framework=torch