Belief manipulation through propositional announcements

Hunter, Aaron (Aaron Hunter (Aaron_Hunter)) (author)
Schwarzentruber, Francois (author)
Tsang, Eric (author)
(editor)
(translator)

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Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) in Melbourne, Australia 19-25 August 2017. Public announcements cause each agent in a group to modify their beliefs to incorporate some new piece of information, while simultaneously being aware that all other agents are doing the same. Given a set of agents and a set of epistemic goals, it is natural to ask if there is a single announcement that will make each agent believe the corresponding goal. This problem is known to be undecidable in a general modal setting, where the presence of nested beliefs can lead to complex dynamics. In this paper, we consider not necessarily truthful public announcements in the setting of AGM belief revision. We prove that announcement finding in this setting is not only decidable, but that it is simpler than the corresponding problem in the most simplified modal logics. We then describe an implemented tool that uses announcement finding to control robot behaviour through belief manipulation.

https://pdfs.semanticscholar.org/145c/3855e7ebdfe0fd71546fd0848ff844e42b...