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Ecole
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A library of Extensible Combinatorial Optimization Learning Environments for using machine learning inside combinatorial optimization solvers.
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Ecole
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2026-03-10 11:38:19
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Ecole Ecole A library for learning inside the SCIP solver Presentation Features About Us Presentation Ecole 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. Rather than trying to predict solutions to combinatorial optimization problems directly, the philosophy behind Ecole is to work in cooperation with the state-of-the-art Mixed Integer Linear Programming solver SCIP that acts as a controllable algorithm. Ecole provide a collection of computationally efficient, ready to use, learning environments that are also easy to extend to define novel objectives. Documentation GitHub Features Easy to use Ecole is accessible in Python, easy to install, and present a familiar OpenAi-Gym like interface. Fast Ecole is written in efficient C++ (SCIP ...
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7 - scip.zib.de, doc.ecole.ai, gym.openai.com, cerc-datascience.polymtl.ca
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