On iterated revision in the AGM framework

Andreas Herzig (1, 2) , Sébastien Konieczny (1) , Laurent Perrussel (1)

1 IRIT-LILaC - Logique, Interaction, Langue et Calcul
2 CNRS - Centre National de la Recherche Scientifique

While AGM belief revision identifies belief states with sets of formulas, proposals for iterated revision are usually based on more complex belief states. In this paper we investigate within the AGM framework several postulates embodying some aspects of iterated revision. Our main results are negative: when added to the AGM postulates, our postulates force revision to be maxichoice (whenever the new piece of information is inconsistent with the current beliefs the resulting belief set is maximal). We also compare our results to revision operators with memory and we investigate some postulates proposed in this framework.

Domains: Artificial Intelligence [cs.AI]

Andreas Herzig, Sébastien Konieczny, Laurent Perrussel. On iterated revision in the AGM framework. 7th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2003), Jul 2003, Aalborg, Denmark. pp.477-488, ⟨10.1007/978-3-540-45062-7_39⟩. ⟨hal-03300685⟩