examples

Examples

Notebooks

To run the notebooks you can simply install the requirements by running (we recommend using a virtual environment):

pip install -r requirements.txt

Then you can start a jupyter notebook by running jupyter notebook from your terminal.

Designing arenas

For a tutorial on how to design experiments and training configurations we provide a jupyter notebook

You can use load_config_and_play.py to visualize a yml configuration for an environment arena. Make sure animalai is installed and run python load_config_and_play.py your_configuration_file.yml which will open the environment in play mode (control with W,A,S,D or the arrows), close the environment by pressing CTRL+C in the terminal.

Animalai-train examples

You will find a training tutorial in this jupyter notebook

We provide two scripts which show how to use animalai_train to train agents:

• train_ml_agents.py uses ml-agents' PPO implementation (or SAC) and can run multiple environments in parralel to speed up the training process
• train_curriculum.py shows how you can add a curriculum to your training loop

To run either of these make sure you have animalai-train installed.

OpenAI Gym and Baselines

You can use the OpenAI Gym interface to train using Baselines or other similar libraries (including Dopamine and Stable Baselines). To do so you'll need to install:

On Linux:

sudo apt-get update && sudo apt-get install cmake libopenmpi-dev python3-dev zlib1g-dev &&
pip install tensorflow==1.14 &&
pip install git+https://github.com/openai/baselines.git@master#egg=baselines-0.1.6

On Mac: TODO

You can then run train_baselines_dqn.py or train_baselines_ppo2.py for examples.