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Generalized Experience Management

  • Author / Creator
    Thue, David J
  • Computer-based interactive environments present a compelling platform for research in Artificial Intelligence. Using games as its domains, this work has traditionally focused on building AI agents that can play games well (e.g., Checkers, Go, or StarCraft). In more recent years, a parallel line of research has aimed to achieve a different goal: to mimic the abilities of human game designers, extending their reach into the run time of the game. By building an AI agent to gather new information and make decisions as their proxy, designers can ensure that their goals are pursued in a way that adapts to each player automatically, while the game is underway. In this dissertation, I present the Generalized Experience Management (GEM) framework, the first mathematical formalization of modifying the dynamics of an interactive environment during end-user play. Moving beyond traditional, ad hoc methods for creating AI agents that manage player experiences, GEM is grounded in the theory of Markov Decision Processes while still remaining practically applicable in both industry and academia. To evaluate the framework and demonstrate its versatility, I present four adaptive systems as instances thereof: two that I designed and tested through controlled user studies, one that was created independently in a commercial video game, and one that was seminal in the domain of Interactive Drama. Finally, I propose and demonstrate a detailed method for evaluating GEM systems, including a new way to distinguish between the effects of player-specific and player-independent adaptation.

  • Subjects / Keywords
  • Graduation date
    2015-06
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/R3D96Z
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Doctoral
  • Department
    • Department of Computing Science
  • Supervisor / co-supervisor and their department(s)
    • Bulitko, Vadim (Computing Science)
  • Examining committee members and their departments
    • Schaeffer, Jonathan (Computing Science)
    • Jhala, Arnav (University of California Santa Cruz)
    • Zaiane, Osmar (Computing Science)
    • Szafron, Duane (Computing Science)
    • Bulitko, Vadim (Computing Science)
    • Spetch, Marcia (Psychology)