Abstract
In possibility theory, there are two kinds of possibilistic causal networks depending if the possibilistic conditioning is based on the minimum or the product operator. Product-based possibilistic networks share the same practical and theoretical features as Bayesian networks. In this paper, we focus on min-based causal networks and propose a propagation algorithm for such networks. The basic idea is first to transform the initial network only into a moral graph. Then, two different procedures, called stabilization and checking consistency, are applied to compute the possibility degree of any variable of interest given some evidence.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
