Evolving personas for player decision modeling

Christoffer Holmgard, Antonios Liapis, Julian Togelius, Georgios N. Yannakakis

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


    This paper explores how evolved game playing agents can be used to represent a priori defined archetypical ways of playing a test-bed game, as procedural personas. The end goal of such procedural personas is substituting players when authoring game content manually, procedurally, or both (in a mixed-initiative setting). Building on previous work, we compare the performance of newly evolved agents to agents trained via Q-learning as well as a number of baseline agents. Comparisons are performed on the grounds of game playing ability, generalizability, and conformity among agents. Finally, all agents' decision making styles are matched to the decision making styles of human players in order to investigate whether the different methods can yield agents who mimic or differ from human decision making in similar ways. The experiments performed in this paper conclude that agents developed from a priori defined objectives can express human decision making styles and that they are more generalizable and versatile than Q-learning and hand-crafted agents.

    Original languageEnglish (US)
    Title of host publicationIEEE Conference on Computatonal Intelligence and Games, CIG
    PublisherIEEE Computer Society
    ISBN (Electronic)9781479935468
    StatePublished - Oct 21 2014
    Event2014 IEEE Conference on Computational Intelligence and Games, CIG 2014 - Dortmund, Germany
    Duration: Aug 26 2014Aug 29 2014

    Publication series

    NameIEEE Conference on Computatonal Intelligence and Games, CIG
    ISSN (Print)2325-4270
    ISSN (Electronic)2325-4289


    Other2014 IEEE Conference on Computational Intelligence and Games, CIG 2014

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Graphics and Computer-Aided Design
    • Computer Vision and Pattern Recognition
    • Human-Computer Interaction
    • Software


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