论文标题
Ecole：一个类似于健身房的库，用于组合优化求解器中的机器学习
Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers
论文作者
论文摘要
我们提出了Ecole，这是一个简化机器学习研究的新库，以进行组合优化。 Ecole揭示了在Markov决策过程中的控制问题中，以通用组合优化求解器中产生的几个关键决策任务。它的界面模仿了流行的Openai Gym图书馆，并且既可以扩展又直观。我们旨在使该图书馆成为标准化平台，它将降低该领域的入境和加速创新。可以在https://www.ecole.ai上找到文档和代码。
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.
