1. An apparatus for making a probabilistic inference based on a belief network including a child node Y and one or more parent nodes X i (i=1,. .. , n) for the child node Y, the apparatus comprising: a processing system configured to receive as input one or more parameters of a causal influence model that describes influence of the parent nodes X i on possible states of the child node Y, and convert the parameters of the causal influence model into one or more entries of a conditional probability table, using a creation function; wherein the child node Y and each of the parent nodes X i (i=1,. .. , n) is one of: a discrete Boolean node having states true and false; a discrete Ordinal node having a plurality of ordered states; and a discrete Categorical node having a plurality of unordered states; and wherein the influence of each of the parent nodes X i on the child node Y is one of a promoting influence and an inhibiting influence.