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Logic is a field studied mainly by researchers and students of philosophy, mathematics and computing. Inductive logic seeks to determine the extent to which the premisses of an argument entail its conclusion, aiming to provide a theory of how one should reason in the face of uncertainty. It has applications to decision making and artificial intelligence, as well as how scientists should reason when not in possession of the full facts. In this book, Jon Williamson embarks on a quest to find a general, reasonable, applicable inductive logic (GRAIL), all the while examining why pioneers such as…mehr

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Produktbeschreibung
Logic is a field studied mainly by researchers and students of philosophy, mathematics and computing. Inductive logic seeks to determine the extent to which the premisses of an argument entail its conclusion, aiming to provide a theory of how one should reason in the face of uncertainty. It has applications to decision making and artificial intelligence, as well as how scientists should reason when not in possession of the full facts. In this book, Jon Williamson embarks on a quest to find a general, reasonable, applicable inductive logic (GRAIL), all the while examining why pioneers such as Ludwig Wittgenstein and Rudolf Carnap did not entirely succeed in this task. Along the way he presents a general framework for the field, and reaches a new inductive logic, which builds upon recent developments in Bayesian epistemology (a theory about how strongly one should believe the various propositions that one can express). The book explores this logic in detail, discusses some key criticisms, and considers how it might be justified. Is this truly the GRAIL? Although the book presents new research, this material is well suited to being delivered as a series of lectures to students of philosophy, mathematics, or computing and doubles as an introduction to the field of inductive logic

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Autorenporträt
Jon Williamson works on causality, probability, logics and reasoning, and their application to science and medicine. He has a BSc in Mathematics (Manchester), an MSc in Philosophy of Science and a PhD in Philosophy (both at King's College London). He worked at King's College London and the London School of Economics before joining the University of Kent in 2005, where he has been Professor of Reasoning, Inference and Scientific Method since 2008. His other books include Bayesian nets and causality (OUP 2005), In defence of objective Bayesianism (OUP 2010) and Probabilistic logics and probabilistic networks (Springer 2011), and he edits the gazette The Reasoner.