Abstract
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.
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de Weerd, H., Verbrugge, R., Verheij, B. (2014). Agent-Based Models for Higher-Order Theory of Mind. In: Kamiński, B., Koloch, G. (eds) Advances in Social Simulation. Advances in Intelligent Systems and Computing, vol 229. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39829-2_19
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DOI: https://doi.org/10.1007/978-3-642-39829-2_19
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