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 summarize
our empirical studies on human nonmonotonic reasoning.