Probabilistic Logic in a Coherent Setting The approach to probability theory followed in this book (which differs radically from the usual one based on a measure theoretic framework) characterizes probability as a linear operator rather than as a measure and is based on the concept of coherence which can be framed in the most general view of conditional probability. It is a `flexible and unifying tool suited for handling e.g. partial probability assessments (not requiring that the set of all possible `outcomes be endowed with a previously given algebraic structure such as a Boolean algebra) and conditional independence in a way that avoids all the inconsistencies related to logical dependence (so that a theory referring to graphical models more general than those usually considered in bayesian networks can be derived). Moreover it is possible to encompass other approaches to uncertain reasoning such as fuzziness possibility functions and default reasoning. The book is kept self contained provided the reader is familiar with the elementary aspects of propositional calculus linear algebra and analysis