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Jeffrey's Rule of Conditioning Generalized to Belief Functions by Smets, Philippe is a scholarly article available to read on EtoBox.

What is Jeffrey's Rule of Conditioning Generalized to Belief Functions about?

Jeffrey's rule of conditioning has been proposed in order to revise a probability measure by another probability function. We generalize it within the framework of the models based on belief functions. We show that several forms of Jeffrey's conditionings can be defined that correspond to the geometrical rule of conditioning and to Dempster's rule of conditioning, respectively.

Author

Smets, Philippe

Published

2013

Language

EN