We, in particular, Kinesso fellow Fedor Grab https://www.linkedin.com/in/fedor-grab-14609b1a4/ have created an open-source auto reinforcement learning library called Kindo. You can see the code and example here https://github.com/NEU-AI-Skunkworks/kindo/tree/master

kindo
Kindo is a reinforcement learning high-level API enabling developers and analysts to use Stable Baselines 3 and TF-Agents algorithms.
Stable Baselines 3 is powered by PyTorch. TF-Agents is powered by Tensorflow 2.X
Kindo enables to train models using both Tensorflow 2.X and PyTorch deep learning frameworks.
Main features
- Training algorithms from both tf_agents and stable_baselines3 packages
- Monitoring and plotting training history, saving it in a consistent format
- stable_baselines3 similar callbacks for both stable_baselines3 and tf_agents
- Open AI gym environments compatibility
- Open AI gym environment from
.csv
file creation - Bandit problems support
Installation
Prerequisites
Kindo requires python 3.8+
Install using pip
pip install git+https://github.com/NEU-AI-Skunkworks/kindo.git@master
Important Information
If you use conda environment, and your kernel was killed with an errorOMP: Error #15: Initializing libiomp5.dylib, but found libomp.dylib already initialized.
Check out this stackoverflow question
Examples
Kindo code example notebook is provided here