  It is well known that conditional independence can be used to factorize a
joint probability into a multiplication of conditional probabilities. This
paper proposes a constructive definition of inter-causal independence, which
can be used to further factorize a conditional probability. An inference
algorithm is developed, which makes use of both conditional independence and
inter-causal independence to reduce inference complexity in Bayesian networks.
