Pivotal Pruning of Trade-offs in QPNs

Abstract

Qualitative probabilistic networks have been designed for probabilistic reasoning in a qualitative way. Due to their coarse level of representation detail, qualitative probabilistic networks do not provide for resolving trade-offs and typically yield ambiguous results upon inference. We present an algorithm for computing more insightful results for unresolved trade-offs. The algorithm builds upon the idea of using pivots to zoom in on the trade-offs and identifying the information that would serve to resolve them.

Appears in Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI2000)

References in corpus (5)

• Bayes-Ball: The Rational Pastime (for Determining Irrelevance and Requisite Information in Belief Networks and Influence Diagrams)
• Computational Advantages of Relevance Reasoning in Bayesian Belief Networks
• Enhancing QPNs for Trade-off Resolution
• Refining Reasoning in Qualitative Probabilistic Networks
• Incremental Tradeoff Resolution in Qualitative Probabilistic Networks