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IJCAI 2007

Conference Paper Uncertainty Artificial Intelligence

Abstract

A general framework for minimisation-based belief change is presented. A problem instance is made up of an undirected graph, where a formula is associated with each vertex. For example, vertices may represent spatial locations, points in time, or some other notion of locality. Information is shared between vertices via a process of minimisation over the graph. We give equivalent semantic and syntactic characterisations of this minimisation. We also show that this approach is general enough to capture existing minimisation-based approaches to belief merging, belief revision, and (temporal) extrapolation operators. While we focus on a set-theoretic notion of minimisation, we also consider other approaches, such as cardinality-based and priority-based minimisation.

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Context

Venue
International Joint Conference on Artificial Intelligence
Archive span
1969-2025
Indexed papers
14525
Paper id
726644655836469387