Metadata-Version: 2.1
Name: bbrl-algos
Version: 0.0.2
Summary: BBRL algos, a library of reinforcement learning algorithms
Author-email: Olivier Sigaud <olivier.sigaud@isir.upmc.fr>, Mathis Koroglu <mathis.koroglu@etu.sorbonne-universite.fr>
Maintainer-email: Olivier Sigaud <olivier.sigaud@isir.upmc.fr>
Project-URL: repository, https://github.com/Arlaz/bbrl_algos
Keywords: reinforcement learning
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Natural Language :: English
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3 :: Only
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: bbrl
Requires-Dist: wandb
Requires-Dist: optuna
Requires-Dist: hydra-core
Provides-Extra: all
Requires-Dist: bbrl ; extra == 'all'
Requires-Dist: wandb ; extra == 'all'
Requires-Dist: optuna ; extra == 'all'
Requires-Dist: hydra-core ; extra == 'all'

# BBRL - ALGOS

## Description

This library is designed for education purposes, it is mainly used to perform some practical experiences with various RL algorithms. It facilitates using optuna for tuning hyper-parameters and using rliable and statistical tests for analyzing the results.

## Installation

git clone https://github.com/osigaud/bbrl_algos.git

cd bbrl_algos

pip install -e .

We suggest using your favorite python environment (conda, venv, ...) as some further installations might be necessary

## Usage

go to src/bbrl_algos, choose your algorithm and run python3 your_algorithm.py
