Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers

Andrea Lodi; Antoine Prouvost; Didier Ch\'etelat; Justin Dumouchelle; Lara Scavuzzo; Maxime Gasse

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arxiv 2011.06069 v2 pith:VL4T5GFC submitted 2020-11-11 cs.LG math.OC

Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers

Antoine Prouvost , Justin Dumouchelle , Lara Scavuzzo , Maxime Gasse , Didier Ch\'etelat , Andrea Lodi This is my paper

classification cs.LG math.OC

keywords ecolelibrarycombinatorialoptimizationdecisionlearningmachinesolvers

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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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