Probabilistic Reasoning with Maximum Entropy - The System PIT

Abstract

We present a system for common sense reasoning based on propositional logic, the probability calculus and the concept of model-quantification. The task of this system PIT (for Probability Induction 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 semantics we know the corresponding decisions to make sense in many problems of common sense reasoning. We will show this with an example from default reasoning and an example of medical diagnosis. 2 Introduction Propositional logic is a well-researched area of science and allows the specification of many kinds of exa..