Abstract
Applying Theory of Mind to multi-agent systems enables agents to model and reason about other agents’ minds. Recent work shows that this ability could increase the performance of agents, making them more efficient than agents that lack this ability. However, modelling others agents’ minds is a difficult task, given that it involves many factors of uncertainty, e.g., the uncertainty of the communication channel, the uncertainty of reading other agents correctly, and the uncertainty of trust in other agents. In this paper, we explore how agents acquire and update Theory of Mind under conditions of uncertainty. To represent uncertain Theory of Mind, we add probability estimation on a formal semantics model for agent communication based on the BDI architecture and agent communication languages.
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Notes
- 1.
Note that our approach is more general than that, in which ToM could be used to implement similar approaches for teamwork, which is a likely research direction for our work.
- 2.
- 3.
Note that we are ignoring any other updates agents execute in their mental attitudes, given we are interested only in the updates agents make on their ToM.
- 4.
In [28], the authors show that trust aggregates not only the sincerity of the source but also the expertise the source has about the information communicated.
- 5.
When considering \(\gamma = 0.1\) and \(\alpha \) and \(\beta >= 0.8\), agents are able to reach shared beliefs communicating only 2 messages.
- 6.
We do not represent the time at which the messages were communicated, but since they were communicated at different times we introduced different values for \(\gamma \).
- 7.
It is similar to committing a type I error in a statistical analysis.
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Acknowledgements
We gratefully acknowledge the partial support from CAPES and CNPq. Special thanks to Francesca Mosca for the support and for the feedback on this paper.
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Sarkadi, Ş., Panisson, A.R., Bordini, R.H., McBurney, P., Parsons, S. (2019). Towards an Approach for Modelling Uncertain Theory of Mind in Multi-Agent Systems. In: Lujak, M. (eds) Agreement Technologies. AT 2018. Lecture Notes in Computer Science(), vol 11327. Springer, Cham. https://doi.org/10.1007/978-3-030-17294-7_1
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