This is a past event
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 talk, we define trust as a pre-processing step before revision. We emphasise 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 relativising 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 examine its properties. In particular, we show how trust-sensitive revision is manipulable, in the sense that agents can sometimes have incentive to pass on misleading information. When multiple reporting agents are involved, we use a distance function over states to represent differing degrees of trust. This ensures that the most trusted reports will be believed. This is joint work with Aaron Hunter.
Bio:
Richard Booth is a lecturer at Mahasarakham University, Thailand. He obtained his PhD in mathematics from Manchester University and has worked in Saarbruecken, Leipzig, Wollongong, Sydney and most recently at the University of Luxembourg. His research interests lie in logic-based approaches to artificial intelligence and knowledge representation, specifically in belief revision, argumentation, nonmonotonic reasoning, reasoning about preferences and description logics.
- Speaker
- Richard Booth
- Hosted by
- Martin Caminada
- Venue
- Meston 011