Adventures of AI Directors Early in the Development of Nightingale

Authors

  • Kristen K. Yu Department of Computing Science, University of Alberta Alberta Machine Intelligence Institute Inflexion Games Inc.
  • Matthew Guzdial Department of Computing Science, University of Alberta Alberta Machine Intelligence Institute
  • Nathan R. Sturtevant Department of Computing Science, University of Alberta Alberta Machine Intelligence Institute Inflexion Games Inc.
  • Morgan Cselinacz Department of Digital Humanities, University of Alberta
  • Chris Corfe Inflexion Games Inc.
  • Izzy Hubert Lyall Inflexion Games Inc.
  • Chris Smith Inflexion Games Inc.

DOI:

https://doi.org/10.1609/aiide.v18i1.21949

Keywords:

AI Directors, Experience Management, Player Modeling, Player Experience, Quests, Reinforcement Learning

Abstract

Players can sometimes engage with parts of a video game that they do not enjoy if the game does not try to adapt the experience to the player’s preference. AI directors have been used in the past to tailor player experience to different people. In industry, AI directors are relatively uncommon and are typically domain-specific and rules-based. In this paper, we present a reinforcement learning-based AI director developed for the industry game Nightingale with the help of Inflexion Games. We ran an experiment to evaluate the effectiveness of the AI director in creating a desired player experience, but found inconclusive evidence. In line with this year’s theme, we present our negative results and their implications for future AI directors, along with general discussion from working closely with an industry partner.

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Published

2022-10-11

How to Cite

Yu, K. K., Guzdial, M., Sturtevant, N. R., Cselinacz, M., Corfe, C., Hubert Lyall, I., & Smith, C. (2022). Adventures of AI Directors Early in the Development of Nightingale. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 18(1), 70-77. https://doi.org/10.1609/aiide.v18i1.21949