A Syntactic Approach to Revising Epistemic States with Uncertain Inputs

Kim Bauters, Weiru Liu, Jun Hong, Lluis Godo, Carles Sierra

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)
276 Downloads (Pure)

Abstract

Revising its beliefs when receiving new information is an important ability of any intelligent system. However, in realistic settings the new input is not always certain. A compelling way of dealing with uncertain input in an agent-based setting is to treat it as unreliable input, which may strengthen or weaken the beliefs of the agent. Recent work focused on the postulates associated with this form of belief change and on finding semantical operators that satisfy these postulates. In this paper we propose a new syntactic approach for this form of belief change and show that it agrees with the semantical definition. This makes it feasible to develop complex agent systems capable of efficiently dealing with unreliable input in a semantically meaningful way. Additionally, we show that imposing restrictions on the input and the beliefs that are entailed allows us to devise a tractable approach suitable for resource-bounded agents or agents where reactiveness is of paramount importance.
Original languageEnglish
Title of host publicationTools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference on
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages154-161
Number of pages8
ISBN (Print)1082-3409
DOIs
Publication statusPublished - 10 Nov 2014
EventTools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference - Limassol, Cyprus
Duration: 10 Nov 201412 Nov 2014

Conference

ConferenceTools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference
Country/TerritoryCyprus
CityLimassol
Period10/11/201412/11/2014

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