A Model for Non-Monotonic Reasoning Using Dempster's Rule
  Considerable attention has been given to the problem of non-monotonic
reasoning in a belief function framework. Earlier work (M. Ginsberg) proposed
solutions introducing meta-rules which recognized conditional independencies in
a probabilistic sense. More recently an e-calculus formulation of default
reasoning (J. Pearl) shows that the application of Dempster's rule to a
non-monotonic situation produces erroneous results. This paper presents a new
belief function interpretation of the problem which combines the rules in a way
which is more compatible with probabilistic results and respects conditions of
independence necessary for the application of Dempster's combination rule. A
new general framework for combining conflicting evidence is also proposed in
which the normalization factor becomes modified. This produces more intuitively
acceptable results.
