Agent-Based Models for Higher-Order Theory of Mind

  • Harmen de WeerdEmail author
  • Rineke Verbrugge
  • Bart Verheij
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 229)


Agent-based models are a powerful tool for explaining the emergence of social phenomena in a society. In such models, individual agents typically have little cognitive ability. In this paper, we model agents with the cognitive ability to make use of theory of mind. People use this ability to reason explicitly about the beliefs, desires, and goals of others. They also take this ability further, and expect other people to have access to theory of mind as well. To explain the emergence of this higher-order theory of mind, we place agents capable of theory of mind in a particular negotiation game known as Colored Trails, and determine to what extent theory of mind is beneficial to computational agents. Our results show that the use of first-order theory of mind helps agents to offer better trades. We also find that second-order theory of mind allows agents to perform better than first-order colleagues, by taking into account competing offers that other agents may make. Our results suggest that agents experience diminishing returns on orders of theory of mind higher than level two, similar to what is seen in people. These findings corroborate those in more abstract settings.


Goal Location Strategic Game Negotiation Game Game Setting Computational Agent 
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 2014

Authors and Affiliations

  • Harmen de Weerd
    • 1
    Email author
  • Rineke Verbrugge
    • 1
  • Bart Verheij
    • 1
  1. 1.Institute of Artificial IntelligenceUniversity of GroningenGroningenNetherlands

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