Abstract
The well-known AGM framework provides an intuitively plausible model of nonmonotonic belief revision, but it has the drawback that it is not computational. A computational variant has been proposed by Hansson, and subsequently Hansson and Wassermann have identified a notion of local belief change and discussed how this can modeled in an adaptation of Hansson framework. Briefly, the belief set is compartmentalized in such a way that consistency may be preserved in one compartment, while inconsistency may be entertained in another compartment without the entire belief system degenerating to the trivial case where all propositions are believed. An alternative to the AGM framework is the Dynamic Reasoning System (DRS), which models reasoning explicitly as a temporal activity. The objective in this paper is to show how the phenomenon of local belief change studied by Hansson and Wassermann can be modeled in the DRS framework.
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Schwartz, D.G., Ustymenko, S. (2012). Modeling Local Belief Revision in a Dynamic Reasoning System. In: Kosseim, L., Inkpen, D. (eds) Advances in Artificial Intelligence. Canadian AI 2012. Lecture Notes in Computer Science(), vol 7310. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30353-1_38
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DOI: https://doi.org/10.1007/978-3-642-30353-1_38
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