Decision making styles as deviation from rational action: A super Mario case study

Christoffer Holmgard, Julian Togelius, Georgios N. Yannakakis

    Research output: Contribution to conferencePaper

    Abstract

    In this paper we describe a method of modeling play styles as deviations from approximations of game theoretically rational actions. These deviations are interpreted as containing information about player skill and player decision making style. We hypothesize that this information is useful for differentiating between players and for understanding why human player behavior is attributed intentionality which we argue is a prerequisite for believability. To investigate these hypotheses we describe an experiment comparing 400 games in the Mario AI Benchmark testbed, played by humans, with equivalent games played by an approximately game theoretically rationally playing AI agent. The player actions' deviations from the rational agent's actions are subjected to feature extraction, and the resulting features are used to cluster play sessions into expressions of different play styles. We discuss how these styles differ, and how believable agent behavior might be approached by using these styles as an outset for a planning agent. Finally, we discuss the implications of making assumptions about rational game play and the problematic aspects of inferring player intentions from behavior.

    Original languageEnglish (US)
    Pages142-148
    Number of pages7
    StatePublished - 2013
    Event9th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2013 - Boston, United States
    Duration: Oct 14 2013Oct 18 2013

    Other

    Other9th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2013
    CountryUnited States
    CityBoston
    Period10/14/1310/18/13

    ASJC Scopus subject areas

    • Visual Arts and Performing Arts
    • Artificial Intelligence

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