Open AccessComputer Science

Niels Justesen, Philip Bontrager, Julian Togelius, Sebastian Risi

2017.8.25IEEE Transactions on Games

DOI: 10.1109/tg.2019.2896986

tlooto Summary

The unique requirements that different game genres pose to a deep learning system are analyzed and important open challenges in the context of applying these machine learning methods to video games, such as general game playing, dealing with extremely large decision spaces and sparse rewards are highlighted.

Abstract

In this paper, we review recent deep learning advances in the context of how they have been applied to play different types of video games such as first-person shooters, arcade games, and real-time strategy games. We analyze the unique requirements that different game genres pose to a deep learning system and highlight important open challenges in the context of applying these machine learning methods to video games, such as general game playing, dealing with extremely large decision spaces and sparse rewards.

Citation format

JUSTESEN, Niels, et al. Deep learning for video game playing [preprint]. arXiv, 2017. arXiv:1708.07902.