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Kalman-like filtering and updating in a possibilistic setting

Salem Benferhat, Didier Dubois, Henri Prade

This paper proposes a qualitative counterpart of Kalman filtering in the possibilistic logic setting. It corresponds to a type of updating involving a prediction step followed by a revision step. This is compared with updating operations based on imaging in the sense of Lewis. Imaging is reconsidered in the perspective of a generalized view of Kalman filtering where it appears as a particular case of Kalman filtering. A syntactic counterpart of qualitative filtering is given in terms of weighted knowledge bases.

Keywords: Uncertainty in AI

Citation: Salem Benferhat, Didier Dubois, Henri Prade: Kalman-like filtering and updating in a possibilistic setting. In W.Horn (ed.): ECAI2000, Proceedings of the 14th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2000, pp.8-12.


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ECAI-2000 is organised by the European Coordinating Committee for Artificial Intelligence (ECCAI) and hosted by the Humboldt University on behalf of Gesellschaft für Informatik.