Introducing situational signs in qualitative probabilistic networks

A qualitative probabilistic network is a graphical model of the probabilistic influences among a set of statistical variables, in which each influence is associated with a qualitative sign. A non-monotonic influence between two variables is associated with the ambiguous sign '?', which indicates that the actual sign of the influence depends on the state of the network. The presence of such ambiguous signs is undesirable as it tends to lead to uninformative results upon inference. In this paper, we argue that, although a non-monotonic influence may have varying effects, in each specific state of the network, its effect is unambiguous. To capture the current effect of the influence, we introduce the concept of situational sign. We show how situational signs can be used upon inference and how they are updated as the state of the network changes. By means of a real-life qualitative network in oncology, we show that the use of situational signs can effectively forestall uninformative results upon inference.