Non-Monotonicity in Probabilistic Reasoning (1988)
by Benjamin N. Grosof
Abstract:
We start by defining an approach to non-monotonic probabilistic
reasoning in terms of non-monotonic categorical (true-false)
reasoning. We identify a type of non-monotonic probabilistic
reasoning, akin to default inheritance, that is commonly found in
practice, especially in "evidential" and "Bayesian" reasoning. We
formulate this in terms of the Maximization of Conditional
Independence (MCI), and identify a variety of applications for this
sort of default. We propose a formalization using Pointwise
Circumscription. We compare MCI to Maximum Entropy, another kind of
non-monotonic principle, and conclude by raising a number of open
questions.
Last update: 1-8-98
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