Foundations of Bayesianism (Q5956948)

[The articles of this volume will not be indexed individually.] This volume includes chapters in four categories: Bayesianism, Causality and Networks, Logic, Mathematics and Bayesianism, Bayesianism and Decision Theory, and Criticisms of Bayesianism. The chapters are contributed by major figures in the field, such as Judea Pearl, ``Bayesianism and causality, or, why I am only a half-Bayesian,'' and Colin Howson, ``The logic of Bayesian probability.'' The editors are to be congratulated on selecting a collection of papers that are all first rate. The three contributions to the fourth section are most striking and least expected. In particular, the chapter by the economist Max Albert, titled ``Bayesian learning and expectation formation: Anything goes,'' defends the thesis that the Bayesian apparatus is vacuous descriptively (``Bayesian rationality becomes empty if the decision maker considers a [large enough] set of hypotheses \(\ldots\).'' [p. 357] Furthermore, he argues that Bayesianism is normatively useless: ``Nobody stands a better chance in any competition just on account of being a Bayesian.'' [p. 357]) That a volume on the foundations of Bayesianism contains such material is surely evidence of the editors' willingness to come to grips with the issues. Contents: \textit{J. Williamson} and \textit{D. Corfield}, ``Introduction: Bayesianism into the 21st century'' (pp. 1-16); \textit{J. Pearl}, ``Bayesianism and causality, or, why I am only a half-Bayesian'' (pp. 19-36); \textit{A. P. Dawid}, ``Causal inference without counterfactuals'' (pp. 37-74); \textit{J. Williamson}, ``Foundations of Bayesian networks'' (pp. 75-115); \textit{P. M. Williams}, ``Probabilistic learning models'' (pp. 117-134); \textit{C. Howson}, ``The logic of Bayesian probability'' (pp. 137-159); \textit{M. C. Galavotti}, ``Subjectivism, objectivism and objectivity in Bruno de Finetti's Bayesianism'' (pp. 161-174); \textit{D. Corfield}, ``Bayesianism in mathematics'' (pp. 175-201); \textit{J. B. Paris} and \textit{A. Vencovská}, ``Common sense and stochastic independence'' (pp. 203-240); \textit{J. Cussens}, ``Integrating probabilistic and logical reasoning'' (pp. 241-260); \textit{R. Bradley}, ``Ramsey and the measurement of belief'' (pp. 263-290); \textit{E. F. McClennen}, ``Bayesianism and independence'' (pp. 291-307); \textit{P. Mongin}, ``The paradox of the Bayesian experts'' (pp. 309-338); \textit{M. Albert}, ``Bayesian learning and expectations formation: Anything goes'' (pp. 341-362); \textit{D. Gillies}, ``Bayesianism and the fixity of the theoretical framework'' (pp. 363-379); \textit{D. G. Mayo} and \textit{M. Kruse}, ``Principles of inference and their consequences'' (pp. 381-403).