1.7 KiB
Unity ML - Agents (Python API)
Python Setup
Requirements
- Jupyter
- docopt
- Matplotlib
- numpy
- Pillow
- Python (2 or 3)
- Tensorflow (1.0+)
Installing Dependencies
To install dependencies, run:
pip install .
or
pip3 install .
If your Python environment doesn't include pip
, see these instructions on installing it.
Provided Jupyter Notebooks
- Basic - Demonstrates usage of
UnityEnvironment
class for launching and interfacing with Unity Environments. - PPO - Used for training agents. Contains an implementation of Proximal Policy Optimization Reinforcement Learning algorithm.
Running each notebook
To launch jupyter, run:
jupyter notebook
Then navigate to localhost:8888
to access each training notebook.
To monitor training progress, run the following from the root directory of this repo:
tensorboard --logdir='./summaries'
Then navigate to localhost:6006
to monitor progress with Tensorboard.
Training PPO directly
To train using PPO without the notebook, run:
python3 ppo.py <env_name> --train
For a list of additional hyperparameters, run:
python3 ppo.py --help
Using Python API
See this wiki page for a detailed description of the functions and uses of the Python API.
Training on AWS
See this related blog post for a description of how to run Unity Environments on AWS EC2 instances with the GPU.