Changes of relational probabilistic belief states and their computation under optimum entropy semantics

Abstract

Coping with uncertain knowledge and changing beliefs is essential for reasoning in dynamic environments. We generalize an approach to adjust probabilistic belief states by use of the relative entropy in a propositional setting to relational languages. As a second contribution of this paper, we present a method to compute such belief changes by considering a dual problem and present first application and experimental results. © 2013 Springer-Verlag Berlin Heidelberg.