Local Bayesian fusion realized via an agent based architecture

Abstract: In the field of reconnaissance and in many other real world applications, information from different possibly heterogenous information sources has to be fused for obtaining adequate results. We present a local Bayesian approach which is realized via an agent based architecture. In analogy to criminalistic investigators, fusion agents elaborate the posterior Degree of Belief of initial hypotheses by local Bayesian mod-elling and local Bayesian fusion. Thereby, the usually high computational complexity of the Bayesian methodology gets reduced significantly. 1 Bayesian Fusion Methodology The aim underlying Bayesian fusion is inferring the “true value ” z ∈ Z of the not directly observable Properties of Interest (PoI) which is to be elaborated in the given fusion task. For an optimal result, prior knowledge d0 and all other available information contributions d1,..., dS have to be used comprehensively. Bayesian theory in general bases upon the admissible interpretation of the nature of proba-bility as Degree of Belief (DoB). Conform with this, all involved quantities are assumed as random and modelled probabilistically by conditional DoB distributions. The DoB of a