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ecole-0.8.1
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مشاهده بیشتر
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مشاهده بیشترتوضیحات
Extensible Combinatorial Optimization Learning Environments
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | ecole-0.8.1 |
| نام | ecole |
| نسخه کتابخانه | 0.8.1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Antoine Prouvost et al. |
| ایمیل نویسنده | - |
| آدرس صفحه اصلی | https://www.ecole.ai |
| آدرس اینترنتی | https://pypi.org/project/ecole/ |
| مجوز | BSD-3-Clause |
.. image:: https://raw.githubusercontent.com/ds4dm/ecole/master/docs/_static/images/ecole-logo.svg
:target: https://www.ecole.ai
:alt: Ecole logo
:width: 30 %
:align: right
Ecole
=====
.. image:: https://github.com/ds4dm/ecole/actions/workflows/continuous-testing.yml/badge.svg
:target: https://github.com/ds4dm/ecole/actions/workflows/continuous-testing.yml
:alt: Test and deploy on Github Actions
Ecole (pronounced [ekɔl]) stands for *Extensible Combinatorial Optimization Learning
Environments* and aims to expose a number of control problems arising in combinatorial
optimization solvers as Markov
Decision Processes (*i.e.*, Reinforcement Learning environments).
Rather than trying to predict solutions to combinatorial optimization problems directly, the
philosophy behind Ecole is to work
in cooperation with a state-of-the-art Mixed Integer Linear Programming solver
that acts as a controllable algorithm.
The underlying solver used is `SCIP <https://scip.zib.de/>`_, and the user facing API is
meant to mimic the `OpenAI Gym <https://gym.openai.com/>`_ API (as much as possible).
.. code-block:: python
import ecole
env = ecole.environment.Branching(
reward_function=-1.5 * ecole.reward.LpIterations() ** 2,
observation_function=ecole.observation.NodeBipartite(),
)
instances = ecole.instance.SetCoverGenerator()
for _ in range(10):
obs, action_set, reward_offset, done, info = env.reset(next(instances))
while not done:
obs, action_set, reward, done, info = env.step(action_set[0])
Documentation
-------------
Consult the `user Documentation <https://doc.ecole.ai>`_ for tutorials, examples, and library reference.
Discussions and help
--------------------
Head to `Github Discussions <https://github.com/ds4dm/ecole/discussions>`_ for interaction with the community: give
and recieve help, discuss intresting envirnoment, rewards function, and instances generators.
Installation
------------
Conda
^^^^^
.. image:: https://img.shields.io/conda/vn/conda-forge/ecole?label=version&logo=conda-forge
:target: https://anaconda.org/conda-forge/ecole
:alt: Conda-Forge version
.. image:: https://img.shields.io/conda/pn/conda-forge/ecole?logo=conda-forge
:target: https://anaconda.org/conda-forge/ecole
:alt: Conda-Forge platforms
.. code-block:: bash
conda install -c conda-forge ecole
All dependencies are resolved by conda, no compiler is required.
Pip wheel (binary)
^^^^^^^^^^^^^^^^^^
Currently unavailable.
Pip source
^^^^^^^^^^^
.. image:: https://img.shields.io/pypi/v/ecole?logo=python
:target: https://pypi.org/project/ecole/
:alt: PyPI version
Building from source requires:
- A `C++17 compiler <https://en.cppreference.com/w/cpp/compiler_support>`_,
- A `SCIP <https://www.scipopt.org/>`__ installation.
.. code-block:: bash
pip install ecole
Other Options
^^^^^^^^^^^^^
Checkout the `installation instructions <https://doc.ecole.ai/py/en/stable/>`_ in the
documentation for more installation options.
Related Projects
----------------
* `OR-Gym <https://github.com/hubbs5/or-gym>`_ is a gym-like library providing gym-like environments to produce feasible solutions
directly, without the need for an MILP solver;
* `MIPLearn <https://github.com/ANL-CEEESA/MIPLearn>`_ for learning to configure solvers.
Use It, Cite It
---------------
.. image:: https://img.shields.io/badge/arxiv-2011.06069-red
:target: https://arxiv.org/abs/2011.06069
:alt: Ecole publication on Arxiv
If you use Ecole in a scientific publication, please cite the Ecole publication
.. code-block:: text
@inproceedings{
prouvost2020ecole,
title={Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers},
author={Antoine Prouvost and Justin Dumouchelle and Lara Scavuzzo and Maxime Gasse and Didier Ch{\'e}telat and Andrea Lodi},
booktitle={Learning Meets Combinatorial Algorithms at NeurIPS2020},
year={2020},
url={https://openreview.net/forum?id=IVc9hqgibyB}
}
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.6 | Python |
نحوه نصب
نصب پکیج whl ecole-0.8.1:
pip install ecole-0.8.1.whl
نصب پکیج tar.gz ecole-0.8.1:
pip install ecole-0.8.1.tar.gz