Towards an Approach for Modelling Uncertain Theory of Mind in Multi-Agent Systems

Sarkadi, Ş., Panisson, A.R., Bordini, R.H., McBurney, P. and Parsons, S. (2019) Towards an Approach for Modelling Uncertain Theory of Mind in Multi-Agent Systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11327 . pp. 3-17. ISSN UNSPECIFIED

Full content URL: http://doi.org/10.1007/978-3-030-17294-7₁

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Item Type:Article
Item Status:Live Archive

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.

Additional Information:cited By 0
Divisions:College of Science
ID Code:38399
Deposited On:31 Oct 2019 15:37

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