Fundamentals of Bayesian Epistemology provides an accessible introduction to the key concepts and principles of the Bayesian formalism. Volume 2 introduces applications of Bayesianism to confirmation and decision theory, then gives a critical survey of arguments for and challenges to Bayesian epistemology.
Fundamentals of Bayesian Epistemology provides an accessible introduction to the key concepts and principles of the Bayesian formalism. Volume 2 introduces applications of Bayesianism to confirmation and decision theory, then gives a critical survey of arguments for and challenges to Bayesian epistemology.
Michael G. Titelbaum is a Vilas Distinguished Achievement Professor in the Department of Philosophy at the University of Wisconsin-Madison. After majoring in philosophy at Harvard, he had a brief career as a high school teacher. He then earned a PhD in philosophy from the University of California, Berkeley, and completed a Visiting Research Fellowship at the Australian National University. He began at UW-Madison in 2009, and was Chair of the Department of Philosophy 2019-2022.
Inhaltsangabe
III Applications 6: Confirmation 7: Decision Theory IV Arguments for Bayesianism 8: Representation Theorems 9: Dutch Book Arguments 10: Accuracy Arguments Challenges and Objections 11: Memory Loss and Self-Location 12: Old Evidence, Logical Omniscience 13: Alternatives to Bayesianism 14: Comparisons, Ranges, Dempster-Shafer
III Applications 6: Confirmation 7: Decision Theory IV Arguments for Bayesianism 8: Representation Theorems 9: Dutch Book Arguments 10: Accuracy Arguments Challenges and Objections 11: Memory Loss and Self-Location 12: Old Evidence, Logical Omniscience 13: Alternatives to Bayesianism 14: Comparisons, Ranges, Dempster-Shafer
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