Credal networks. - Cozman, Fabio G. (Artificial intelligence.)
This paper presents a complete theory of previous termcredal networksnext term, structures that associate convex sets of probability measures with directed acyclic graphs. previous termCredal networksnext term are graphical models for precise/imprecise beliefs. The main contribution of this work is a theory of previous termcredal networksnext term that displays as much flexibility and representational power as the theory of standard Bayesian previous termnetworks.next term Results in this paper show how to express judgements of irrelevance and independence, and how to compute inferences in previous termcredal networks.next term A previous termcredal networknext term admits several extensions?several sets of probability measures comply with the constraints represented by a previous termnetwork.next term Two types of extensions are investigated. The properties of strong extensions are clarified through a new generalization of d-separation, and exact and approximate inference methods are described for strong extensions. Novel results are presented for natural extensions, and linear fractional programming methods are described for natural extensions. The paper also investigates previous termcredal networksnext term that are defined globally through perturbations of a single previous termnetwork.next term