WHERE WE STAND AT PROBABILISTIC REASONING

Bayes-Nets are a suitable means for probabilistic inference. Such nets are very restricted concerning the communicationlanguage with the user, however. MinREnt-inference in a conditional environment is a powerfulcounterpart to this concept. Here conditional expressions of high complexity instead of mere potential tablesin a directed acyclic graph, permit rich communication between system and user. This is true as well forknowledge acquisition as for query and response. For any such step of probabilistic reasoning, processedinformation is measurable in the information theoretical unit [bit]. The expert-system-shell SPIRIT is a professionaltool for such inference and allows realworld (decision-)models with umpteen variables and hundredsof rules......