Foundations of Bayesianism (Hardcover)

Editorial Foreword. Editorial Preface. Introduction: Bayesianism into the 21st Century; J. Williamson, D. Corfield. Bayesianism, Causality and Networks. Bayesianism and Causality, or, Why I am only a Half-Bayesian; J. Pearl. Causal Inference without Counterfactuals; P. Dawid. Foundations for Bayesian Networks; J. Williamson. Probabilistic Learning Models; P. Williams. Logic, Mathematics and Bayesianism. The Logic of Bayesian Probability; C. Howson. Subjectivism, Objectivism and Objectivity in Bruno de Finetti's Bayesianism; M.C. Galavotti. Bayesianism in Mathematics; D. Corfield. Common Sense and Stochastic Independence; J. Paris, A. Vencovska. Integrating Probabilistic and Logical Reasoning; J. Cussens. Bayesianism and Decision Theory. Ramsey and the Measurement of Belief; R. Bradley. Bayesianism and Independence; E.F. McClennen. The Paradox of the Bayesian Experts; P. Mongin. Criticisms of Bayesianism. Bayesian Learning and Expectations Formation: Anything Goes; M. Albert. Bayesianism and the Fixity of the Theoretical Framework; D. Gillies. Principles of Inference and their Consequences; D. Mayo, M. Kruse. Index.