Skip to main content

BBRL algos, a library of reinforcement learning algorithms

Project description

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

bbrl_algos-0.0.2-py3-none-any.whl (1.0 MB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page