Evaluation of a recommender system for assisting novice game designers

Tiago Machado, Daniel Gopstein, Angela Wang, Oded Nov, Andrew Nealen, Julian Togelius

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Game development is a complex task involving multiple disciplines and technologies. Developers and researchers alike have suggested that AI-driven game design assistants may improve developer workflow. We present a recommender system for assisting humans in game design as well as a rigorous human subjects study to validate it. The AI-driven game design assistance system suggests game mechanics to designers based on characteristics of the game being developed. We believe this method can bring creative insights and increase user's productivity. We conducted quantitative studies that showed the recommender system increases users' levels of accuracy and computational affect, and decreases their levels of workload.

Original languageEnglish (US)
Title of host publicationProceedings of the 15th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2019
PublisherAAAI press
Pages167-173
Number of pages7
ISBN (Electronic)9781577358190
StatePublished - 2019
Event15th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2019 - Atlanta, United States
Duration: Oct 8 2019Oct 12 2019

Publication series

NameProceedings of the 15th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2019

Conference

Conference15th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2019
Country/TerritoryUnited States
CityAtlanta
Period10/8/1910/12/19

ASJC Scopus subject areas

  • Visual Arts and Performing Arts
  • Artificial Intelligence

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