Towards a mental probability logic

Abstract

We propose probability logic as an appropriate standard of reference for evaluating human inferences. Probability logical accounts of nonmonotonic reasoning with SYSTEM P, and conditional syllogisms (MODUS PONENS, etc.) are explored. Furthermore, we present categorical syllogisms with intermediate quantifiers, like the "MOST …" quantifier. While most of the paper is theoretical and intended to stimulate psychological studies, we also summarize our empirical studies on human nonmonotonic reasoning.