MultiStyle: Characterizing Multiplayer Cooperative Gameplay by Incorporating Distinct Player Playstyles in a Multi-Agent Planner

Authors

  • Eric W. Lang School of Computing, University of Utah
  • R. Michael Young School of Computing, University of Utah Entertainment Arts and Engineering Program, University of Utah

DOI:

https://doi.org/10.1609/aiide.v19i1.27505

Keywords:

Player Playstyles, Multi-Agent Planning, Preference-Based Planning, Heuristic Search

Abstract

This paper presents MultiStyle, a multi-agent centralized heuristic search planner that incorporates distinct agent playstyles to generate solution plans where characters express individual preferences while cooperating to reach a goal. We include algorithmic details, an example domain, and multiple different solution plans generated with unique agent playstyle sets. We discuss our intent to incorporate this planner in a tool for game level designers to help them anticipate and understand how teams of players with distinct playstyles may play through their levels. Ultimately, MultiStyle generates solution plans with a novel and increased expressive range by attempting to satisfy sets of action and proposition preferences for each agent.

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Published

2023-10-06

How to Cite

Lang, E. W., & Young, R. M. (2023). MultiStyle: Characterizing Multiplayer Cooperative Gameplay by Incorporating Distinct Player Playstyles in a Multi-Agent Planner. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 19(1), 97-106. https://doi.org/10.1609/aiide.v19i1.27505