Paper
Total Belief Theorem and Generalized Bayes' Theorem
Publication Date:
Publication Date
September 2018
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Abstract
This paper presents two new theoretical contributions for reasoning under uncertainty: 1) the Total Belief Theorem (TBT) which is a direct generalization of the Total Probability Theorem, and 2) the Generalized Bayes' Theorem drawn from TBT. A constructive justification of Fagin-Halpern belief conditioning formulas proposed in the nineties is also given. We also show how our new approach and formulas work through simple illustrative examples.
Description
2018 21st International Conference on Information Fusion (FUSION), July 2018, doi: 10.23919/ICIF.2018.8455351