Abstract
We introduce a numerical framework for possibilistic abduction that is based on a relational setting for handling imprecise data and an information-compression view of possibility distributions as onepoint coverages of random sets. Existing dependencies among disorders, manifestations, and intermediary characteristics are modelled with the aid of a hypergraph representation. The underlying reasoning concept of a possibilistic focusing system is outlined and compared with two alternative approaches in this field.
This work has partially been funded by CEC-ESPRIT III Basic Research Project 6156 (DRUMS II)
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© 1995 Springer-Verlag Berlin Heidelberg
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Gebhardt, J., Kruse, R. (1995). A numerical framework for possibilistic abduction. In: Bouchon-Meunier, B., Yager, R.R., Zadeh, L.A. (eds) Advances in Intelligent Computing — IPMU '94. IPMU 1994. Lecture Notes in Computer Science, vol 945. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0035961
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DOI: https://doi.org/10.1007/BFb0035961
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