On the Formal Semantics of Theory of Mind in Agent Communication

Alison R. Panisson, Stefan Sarkadi, Peter John McBurney, Simon Dominic Parsons, Rafael H. Bordini

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

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Abstract

Recent studies have shown that applying Theory of Mind to agent technologies enables agents to model and reason about other agents' minds, making them more efficient than agents that do not have this ability or agents that have a more limited ability of modelling others' minds. Apart from the interesting results of combining Theory of Mind and agent technologies, an important premise has not been yet fully investigated in the AI literature: how do agents acquire and update their models of others' minds? In the context of multi-agent systems, one of the most natural ways in which agents can acquire models of other agents' mental attitudes is through communication. In this work, we propose an operational semantics for agents to update Theory of Mind through communication. We not only make our formalisation broadly applicable by defining a formal semantics based on components from the BDI architecture, but we also implement our approach in an agent-oriented programming language that is based on that architecture.
Original languageEnglish
Title of host publicationProceedings of the 6th International Conference on Agreement Technologies
Subtitle of host publicationco-located with EUMAS 2018
Number of pages15
Publication statusPublished - 6 Dec 2018

Keywords

  • Theory of Mind
  • Machine Theory of Mind
  • Multi-Agent Systems
  • Agent-Oriented Programming Languages

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