Hybrid Possibilistic Networks

Salem Benferhat, Salma Smaoui

Possibilistic networks are important tools for dealing with uncertain pieces of information. For multiply-connected networks, it is well known that the inference process is a hard problem. This paper studies a new representation of possibilistic networks, called hybrid possibilistic networks. The uncertainty is no longer represented by local conditional possibility distributions, but by their compact representations which are possibilistic knowledge bases. We show that the inference algorithm in hybrid networks is strictly more efficient than the ones of standard propagation algorithm.

Content Area: 10. Knowledge Representation & Reasoning

Subjects: 3.5 Qualitative Reasoning

Submitted: May 6, 2005

This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.