Inductive logic is a theory of how one should reason in the face of uncertainty. It has applications to decision making and artificial intelligence, as well as to scientific problems.
Inductive logic is a theory of how one should reason in the face of uncertainty. It has applications to decision making and artificial intelligence, as well as to scientific problems.
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.
Inhaltsangabe
1: Classical Inductive Logic 2: Logic and Probability 3: Combining Probability and Logic 4: Carnap's Programme 5: From Objective Bayesian Epistemology to Inductive Logic 6: Logical Entailment 7: Inductive Entailment 8: Criticisms of Inductive Logic 9: Justifcation 10: Conclusion
