Probabilistic inference in the physical simulation of interdependent critical infrastructure systems

Abstract

One of the main tasks that can be performed with a Bayesian Network (BN) is the probabilistic inference of unobserved values given evidence. Recently, a framework for physical simulation of critical infrastructures was introduced, accounting for interdependencies and uncertainty; this framework includes the modeling of the interconnected components of a critical infrastructure network as a BN. In this paper we address the problem of the triangulation of the resulting BN, that is the first step in many exact inference algorithms. © 2014 Springer International Publishing.