| Abstract: |
In this paper we consider the inference rules of System P in the framework of
coherent imprecise probabilistic assessments. Exploiting our algorithms, we
propagate the lower and upper probability bounds associated with the
conditional assertions of a given knowledge base, automatically obtaining the
precise probability bounds for the derived conclusions of the inference rules.
This allows a more flexible and realistic use of System P in
default reasoning and provides an exact illustration of the degradation of
the inference rules when interpreted in probabilistic terms. We also examine
the disjunctive Weak Rational Monotony of System
P + proposed by Adams in his extended probability logic.
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