Credibility Models

We present a general hierarchical Bayesian model where Intelligence Sources make Re- ports about events or states in the world, which we call Hypotheses. The underlying multi-entity Bayes net for even a simple sce- nario has hundreds of nodes. We hide the details via Wigmore diagrams and a Google Maps GUI. Our application domain is Intel- ligence data fusion in asymmetrical warfare (terrorism). Some Hypotheses - like whether a village is a threat - may be abstract or un- observable. For these, we define Indicators - more observable Hypotheses whose value has some bearing on the target Hypothesis. The hierarchy can be arbitrarily deep, and Re- ports can provide evidence at any level. Fur- thermore, all Sources have credibility models. Traditional Sources are physical sensors with well-known error models. Non-traditional Sources include humans, websites, news, etc. For these Sources, our credibility models in- clude Hypotheses about unknown factors like objectivity, competence, accuracy, reliabil- ity, and veracity. Every Report by a Source provides evidence about those factors. So, for example, successful ad hominem attacks against one Source can undermine his assur- ances that a village is safe, and lead us to believe it is hostile after all.