Matching Games and Algorithms for General Video Game Playing

Philip Bontrager, Ahmed Khalifa, Andre Mendes, Julian Togelius

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

    Abstract

    This paper examines the performance of a number of AI agents on the games included in the General Video Game Playing Competition. Through analyzing these results, the paper seeks to provide insight into the strengths and weaknesses of the current generation of video game playing algorithms. The paper also provides an analysis of the given games in terms of inherent features which define the different games. Finally, the game features are matched with AI agents, based on performance, in order to demonstrate a plausible case for algorithm portfolios as a general video game playing technique.

    Original languageEnglish (US)
    Title of host publicationProceedings of the 12th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2016
    EditorsNathan Sturtevant, Brian Magerko
    PublisherAssociation for the Advancement of Artificial Intelligence
    Pages122-128
    Number of pages7
    ISBN (Electronic)9781577357728
    StatePublished - Oct 8 2016
    Event12th Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2016 - Burlingame, United States
    Duration: Oct 8 2016Oct 12 2016

    Publication series

    NameProceedings - AAAI Artificial Intelligence and Interactive Digital Entertainment Conference, AIIDE
    ISSN (Print)2326-909X
    ISSN (Electronic)2334-0924

    Conference

    Conference12th Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2016
    Country/TerritoryUnited States
    CityBurlingame
    Period10/8/1610/12/16

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Graphics and Computer-Aided Design
    • Computer Science Applications
    • Human-Computer Interaction
    • Software

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