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
1 maintainer
Metadata
1 maintainer
Release files for bbrl-algos 0.0.2
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Release files / bbrl_algos-0.0.2-py3-none-any.whl
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| Size | 1.0 MB |
| Tags | Python 3 |
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