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arXiv Open Access 2020

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

Antoine Prouvost Justin Dumouchelle Lara Scavuzzo Maxime Gasse Didier Chételat +1 lainnya
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Abstrak

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.

Topik & Kata Kunci

cs.LG math.OC

Penulis (6)

A

Antoine Prouvost

J

Justin Dumouchelle

L

Lara Scavuzzo

M

Maxime Gasse

D

Didier Chételat

A

Andrea Lodi

Format Sitasi

APA MLA BibTeX
Prouvost, A., Dumouchelle, J., Scavuzzo, L., Gasse, M., Chételat, D., Lodi, A. (2020). Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers. https://arxiv.org/abs/2011.06069

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Informasi Jurnal
Tahun Terbit
2020
Bahasa
en
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arXiv
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Open Access ✓