  The DUCK-calculus presented here is a recent approach to cope with
probabilistic uncertainty in a sound and efficient way. Uncertain rules with
bounds for probabilities and explicit conditional independences can be
maintained incrementally. The basic inference mechanism relies on local bounds
propagation, implementable by deductive databases with a bottom-up fixpoint
evaluation. In situations, where no precise bounds are deducible, it can be
combined with simple operations research techniques on a local scope. In
particular, we provide new precise analytical bounds for probabilistic
entailment.
