research-article

Galactic Arms Race: an experiment in evolving video game content

Authors:

Erin J. Hastings,

Kenneth O. StanleyAuthors Info & Claims

ACM SIGEVOlution, Volume 4, Issue 4

Pages 2 - 10

https://doi.org/10.1145/1810136.1810137

Published: 01 March 2010 Publication History

Abstract

Galactic Arms Race (GAR) is an indie video game developed by the Evolutionary Complexity Research Group (EPlex) at the University of Central Florida to demonstrate the potential for novel artificial intelligence (AI) technology to impact video games. In particular, the new technology in GAR is an evolutionary algorithm called content-generating neuroevolution of augmenting topologies (cgNEAT), which is designed to evolve unique game content as the game is played. GAR is a multi-player space shooter in which players fight with particle-system weapons. The unique feature of GAR is that the game continually introduces new such weapons evolved by the cgNEAT algorithm. The philosophy behind GAR is that one of the best ways to support the argument that novel AI algorithms can impact how games are made is to make a fun game that is not only an academic proof-of-concept, but also a genuinely entertaining experience for regular gamers.

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Cited By

Palma SRipamonti LBorghese NMaggiorini DGadia D(2021)Player behaviour metrics for adjusting content in VR games: the case of fearProceedings of the 14th Biannual Conference of the Italian SIGCHI Chapter10.1145/3464385.3464705(1-6)Online publication date: 11-Jul-2021
https://dl.acm.org/doi/10.1145/3464385.3464705
Smith BNayar SRekimoto JIgarashi TWobbrock JAvrahami D(2016)Mining Controller Inputs to Understand GameplayProceedings of the 29th Annual Symposium on User Interface Software and Technology10.1145/2984511.2984543(157-168)Online publication date: 16-Oct-2016
https://dl.acm.org/doi/10.1145/2984511.2984543

Galactic Arms Race: an experiment in evolving video game content

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Published In

cover image ACM SIGEVOlution

ACM SIGEVOlution Volume 4, Issue 4

March 2010

17 pages

EISSN:1931-8499

DOI:10.1145/1810136

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Copyright © 2010 Authors.

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Association for Computing Machinery

New York, NY, United States

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Published: 01 March 2010

Published in SIGEVO Volume 4, Issue 4

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Cited By

Palma SRipamonti LBorghese NMaggiorini DGadia D(2021)Player behaviour metrics for adjusting content in VR games: the case of fearProceedings of the 14th Biannual Conference of the Italian SIGCHI Chapter10.1145/3464385.3464705(1-6)Online publication date: 11-Jul-2021
https://dl.acm.org/doi/10.1145/3464385.3464705
Smith BNayar SRekimoto JIgarashi TWobbrock JAvrahami D(2016)Mining Controller Inputs to Understand GameplayProceedings of the 29th Annual Symposium on User Interface Software and Technology10.1145/2984511.2984543(157-168)Online publication date: 16-Oct-2016
https://dl.acm.org/doi/10.1145/2984511.2984543

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