Ecole: A Gym-like Library for Machine Learning in Combinatorial
Optimization Solvers
- URL: http://arxiv.org/abs/2011.06069v2
- Date: Tue, 24 Nov 2020 21:06:00 GMT
- Title: Ecole: A Gym-like Library for Machine Learning in Combinatorial
Optimization Solvers
- Authors: Antoine Prouvost, Justin Dumouchelle, Lara Scavuzzo, Maxime Gasse,
Didier Ch\'etelat, Andrea Lodi
- Abstract summary: Ecole is a new library to simplify machine learning research for optimization.
Ecole exposes several key decision tasks arising in general-purpose optimization solvers as control problems over Markov decision processes.
We aim to make this library a standardized platform that will lower the bar of entry and accelerate innovation in the field.
- Score: 5.532198590851521
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We present Ecole, a new library to simplify machine learning research for
combinatorial optimization. Ecole exposes several key decision tasks arising in
general-purpose combinatorial optimization solvers as control problems over
Markov decision processes. Its interface mimics the popular OpenAI Gym library
and is both extensible and intuitive to use. We aim at making this library a
standardized platform that will lower the bar of entry and accelerate
innovation in the field. Documentation and code can be found at
https://www.ecole.ai.
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