Visualizing AI Playtesting Data of 2D Side-scrolling Games

Shivam Agarwal, Christian Herrmann, Gunter Wallner, Fabian Beck

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Human playtesting is a useful step in the game development process, but involves high economic costs and is time-consuming. While playtesting through artificial intelligence is gaining attention, it is challenging to analyze the collected data. We address the challenge by proposing visualizations to derive insights about level design in 2D side-scrolling games. To focus on the navigation behavior in the level design, we study the trajectories of computer agents trained using artificial intelligence. We demonstrate the effectiveness of our approach by implementing a web-based prototype and presenting the insights gained from the visualizations for the game Sonic the Hedgehog 2. We highlight lessons learned and directions to customize the approach for other analysis goals of playtesting.

Original languageEnglish
Title of host publicationIEEE Conference on Games, CoG 2020
PublisherIEEE Computer Society
Pages572-575
Number of pages4
ISBN (Electronic)9781728145334
DOIs
Publication statusPublished - Aug 2020
Event2020 IEEE Conference on Games, CoG 2020 - Virtual, Osaka, Japan
Duration: 24 Aug 202027 Aug 2020

Conference

Conference2020 IEEE Conference on Games, CoG 2020
CountryJapan
CityVirtual, Osaka
Period24/08/2027/08/20

Keywords

  • artificial intelligence
  • playtesting
  • visualization

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