Deriving stochastic properties from behavior models defined by Monterey Phoenix

Abstract

Stochastic properties of behavior models are of interest to the developer of a System of Systems (SoS) in order to gain insight to the likelihood of potential outcomes of the system. Constraints added to the system introduce changes to the inherent dependencies within a representative Bayesian belief network; thereby impacting the system. This paper defines a probability process model that may be used to identify the probability of outcomes compliant with behavior models defined in Monterey Phoenix (MP), with constraints added to the model.