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Belief revision and information fusion on optimum entropy

✍ Scribed by Gabriele Kern-Isberner; Wilhelm Rödder

Publisher
John Wiley and Sons
Year
2004
Tongue
English
Weight
165 KB
Volume
19
Category
Article
ISSN
0884-8173

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✦ Synopsis

This article presents new methods for probabilistic belief revision and information fusion. By making use of the information theoretical principles of optimum entropy (ME principles), we define a generalized revision operator that aims at simulating the human learning of lessons, and we introduce a fusion operator that handles probabilistic information faithfully. This ME-fusion operator satisfies basic demands, such as commutativity and the Pareto principle. A detailed analysis shows it to merge the corresponding epistemic states. Furthermore, it induces a numerical fusion operator that computes the information theoretical mean of probabilities.

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