MINERVA: An out-of-the-box GUI tool for data-driven deep reinforcement learning

MINERVA is an Out-of-the-box GUI Tool for Data-Driven Deep Reinforcement Learning, designed for everyone including non-programmers to do reinforcement learning as a tool.

Documentation: https://minerva-ui.readthedocs.io

key features

⚡ All You Need Is Dataset

MINERVA only requires datasets to start data-driven deep reinforcement learning. Any combinations of vector observations and image observations with discrete actions and continuous actions are supported.

🔰 Stunning GUI

MINERVA provides designed with intuitive GUI to let everyone lerverage extremely powerful algorithms without barriers. The GUI is developed as a Single Page Application (SPA) to make it work in the eye-opening speed.

🚀 Powerful Algorithm

MINERVA is powered by d3rlpy, a powerful data-driven deep reinforcement learning library for Python, to provide extremely powerful algorithms in an out-of-the-box way. The trained policy can be exported as TorchScript and ONNX.

installation

$ pip install minerva

update guide

If you update MINERVA, the database schema should be also updated as follows:

$ pip install -U minerva
$ minerva upgrade-db

usage

run server

At the first time, ~/.minerva will be automatically created to store database, uploaded datasets and training metrics.

$ minerva run

You can change the host and port with --host and --port arguments respectively.

delete data

You can delete entire data (~/.minerva) as follows:

$ minerva clean

contributions

build

$ npm install
$ npm run build

coding style

This repository is fully formatted with yapf and standard. You can format the entire scripts as follows:

$ ./scripts/format

lint

This repository is fully analyzed with Pylint, ESLint and sass-lint. You can run analysis as follows:

$ ./scripts/lint

test

The unit tests are provided as much as possible. This repository is using pytest-cov instead of pytest. You can run the entire tests as follows:

$ ./scripts/test

acknowledgement

This work is supported by Information-technology Promotion Agency, Japan (IPA), Exploratory IT Human Resources Project (MITOU Program) in the fiscal year 2020.