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.