Trust as a precursor to belief revision

Booth, Richard ORCID: https://orcid.org/0000-0002-6647-6381 and Hunter, Aaron 2018. Trust as a precursor to belief revision. Journal of Artificial Intelligence Research 61 , pp. 699-722. 10.1613/jair.5521

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Abstract

Belief revision is concerned with incorporating new information into a pre-existing set of beliefs. When the new information comes from another agent, we must first determine if that agent should be trusted. In this paper, we define trust as a pre-processing step before revision. We emphasize that trust in an agent is often restricted to a particular domain of expertise. We demonstrate that this form of trust can be captured by associating a state partition with each agent, then relativizing all reports to this partition before revising. We position the resulting family of trust-sensitive revision operators within the class of selective revision operators of Ferme and Hansson, and we prove a representation result that characterizes the class of trust-sensitive revision operators in terms of a set of postulates. We also show that trust-sensitive revision is manipulable, in the sense that agents can sometimes have incentive to pass on misleading information.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Publisher:	AI Access Foundation
ISSN:	1076-9757
Related URLs:	http://www.jair.org/
Date of First Compliant Deposit:	3 November 2017
Date of Acceptance:	5 August 2017
Last Modified:	17 Nov 2024 16:45
URI:	https://orca.cardiff.ac.uk/id/eprint/106153

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