Incremental Tradeoff Resolution in Qualitative Probabilistic Networks

Abstract

Qualitative probabilistic reasoning in a Bayesian net- work often reveals tradeoffs: relationships that are ambiguous due to competing qualitative influences. We present two techniques that combine qualitative and numeric probabilistic reasoning to resolve such tradeoffs, inferring the qualitative relationship be- tween nodes in a Bayesian network. The first approach incrementally marginalizes nodes in network, and the second incrementally refines the state spaces of ran- dom variables. Both provide systematic methods for tradeoff resolution at potentially lower computational cost than application of purely numeric methods.