
An Inequality Paradigm for Probabilistic Knowledge (1986) 
    by Benjamin N. Grosof 
Abstract:
We propose an inequality paradigm for probabilistic reasoning based on 
a a logic of upper and lower bounds on conditional probabilities.  We investigate
a family of probabilistic logics, generalizing the work of Nilsson.  We develop
a variety of logical notions for probabilistic reasoning, including soundness;
completeness; and justification; and convergence:  reduction of a theory
to a simpler logical class.  We argue that a bounds view is especially useful
for describing the semantics of probabilistic knowledge representation and for
describing intermediate states of probabilistic inference and updating.
We show that the Dempter-Shafer theory of evidence is formally identical to 
a special case of our generalized probabilistic logic.  Our paradigm thus
incorporates both Bayesian "rule-based" approaches and avowedly non-Bayesian
"evidential" approaches such as MYCIN and Dempster-Shafer.  We suggest how
to integrate the two "schools", and explore some possibilities for novel
synthesis of a variety of ideas in probabilistic reasoning.
Last update: 1-8-98
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