Depth in strategic games

Frank Lantz, Aaron Isaksen, Alexander Jaffe, Andy Nealen, Julian Togelius

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

    Abstract

    This paper explores the question of whether it's possible to discover a well-defined property of game systems that corresponds to what game designers and players mean by the term "depth." We propose a measurable property of a game's formal system, which we call '<f\ that corresponds to the capacity of a game to absorb dedicated problem-solving attention and allow for sustained, long-term learning. To define this property we develop a formal model that measures how susceptible a game is to partial solutions under conditions of steadily increasing computational resources. We then sketch out several directions for using the model to investigate questions about the structural properties of games that produce these effects.

    Original languageEnglish (US)
    Title of host publicationWS-17-01
    Subtitle of host publicationArtificial Intelligence and Operations Research for Social Good; WS-17-02: Artificial Intelligence, Ethics, and Society; WS-17-03: Artificial Intelligence for Connected and Automated Vehicles; WS-17-04: Artificial Intelligence for Cyber Security; WS-17-05: Artificial Intelligence for Smart Grids and Buildings; WS-17-06: Computer Poker and Imperfect Information Games; WS-17-07: Crowdsourcing, Deep Learning and Artificial Intelligence Agents; WS-17-08: Distributed Machine Learning; WS-17-09: Joint Workshop on Health Intelligence; WS-17-10: Human-Aware Artificial Intelligence; WS-17-11: Human-Machine Collaborative Learning; WS-17-12: Knowledge-Based Techniques for Problem Solving and Reasoning; WS-17-13: Plan, Activity, and Intent Recognition; WS-17-14: Symbolic Inference and Optimization; WS-17-15: What's Next for AI in Games?
    PublisherAI Access Foundation
    Pages967-974
    Number of pages8
    ISBN (Electronic)9781577357865
    StatePublished - 2017
    Event31st AAAI Conference on Artificial Intelligence, AAAI 2017 - San Francisco, United States
    Duration: Feb 4 2017Feb 10 2017

    Publication series

    NameAAAI Workshop - Technical Report
    VolumeWS-17-01 - WS-17-15

    Other

    Other31st AAAI Conference on Artificial Intelligence, AAAI 2017
    Country/TerritoryUnited States
    CitySan Francisco
    Period2/4/172/10/17

    ASJC Scopus subject areas

    • Engineering(all)

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