Explaining and Predicting the Behavior of BDI-Based Agents in Role-Playing Games

  • Michal P. Sindlar
  • Mehdi M. Dastani
  • Frank Dignum
  • John-Jules Ch. Meyer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5948)


Virtual characters in games operate in a social context involving other characters and possibly human players as well. If such socially situated virtual characters are to be considered believable to players, they should appear to adjust their behavior based on their (presumed) beliefs about the mental states of other characters. Autonomous BDI-based agents are suitable for modeling characters that base their actions on mental states attributed to other agents. In this paper, it is illustrated how agent-based characters can infer the mental state of other virtual characters by observing others’ actions in the context of some scene in a role-playing game. Contextual information can be utilized in explanation and prediction of agents’ behavior, and as such can form the basis for developing characters that appear to be socially aware.


Autonomous Agent Predictive Function Virtual Character Behavioral Rule Behavioral Description 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Michal P. Sindlar
    • 1
  • Mehdi M. Dastani
    • 1
  • Frank Dignum
    • 1
  • John-Jules Ch. Meyer
    • 1
  1. 1.University of UtrechtUtrechtThe Netherlands

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