TorchCraft: a Library for Machine Learning Research on Real-Time Strategy Games
Machine Learning
2016-11-07 v2 Artificial Intelligence
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.
Keywords
Cite
@article{arxiv.1611.00625,
title = {TorchCraft: a Library for Machine Learning Research on Real-Time Strategy Games},
author = {Gabriel Synnaeve and Nantas Nardelli and Alex Auvolat and Soumith Chintala and Timothée Lacroix and Zeming Lin and Florian Richoux and Nicolas Usunier},
journal= {arXiv preprint arXiv:1611.00625},
year = {2016}
}