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arXiv · 1611.00625

TorchCraft: a Library for Machine Learning Research on Real-Time Strategy Games

Gabriel Synnaeve·Nantas Nardelli·Alex Auvolat·Soumith Chintala·Timothée Lacroix·Zeming Lin·Florian Richoux·Nicolas Usunier
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Abstract

We present TorchCraft, a library that enables deep learning research on Real-Time Strategy (RTS) games such as StarCraft: Brood War, by making it easier to control these games from a machine learning framework, here Torch. This white paper argues for using RTS games as a benchmark for AI research, and describes the design and components of TorchCraft.

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Gabriel Synnaeve, Nantas Nardelli, Alex Auvolat, Soumith Chintala, Timothée Lacroix, Zeming Lin, Florian Richoux, Nicolas Usunier. 2016-11-01. TorchCraft: a Library for Machine Learning Research on Real-Time Strategy Games. https://arxiv.org/abs/1611.00625

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