Probabilistic Reasoning with Maximum Entropy - The System PIT (system description)
by Manfred Schramm und Volker Fischer Technische Universität München, Germany
Abstract
We present a system for common sense reasoning based on propositional logic, the probability cal-
culus and the concept of model-quantification. The task of this system PIT (for Probability Induc-
tion Tool) is to deliver decisions under incomplete knowledge but to keep the necessary additional
assumptions as minimal as possible. Following this task it shows non-monotonic behavior in two
ways: Non-monotonic decisions can be the result of reasoning in a single probability model (via
conditionalization) or in a set of probability models (via additional principles of rational decisions,
justified by model-quantification). As the concept of modelquantification delivers a precise seman-
tics we know the corresponding decisions to make sense in many problems of common sense rea-
soning. We will show this with an example from default reasoning and an example of medical
diagnosis.