Coping with uncertainty is a necessary part of ordinary life and is crucial to an understanding of how the mind works. For example, it is a vital element in developing artificial intelligence that will not be undermined by its own rigidities. There have been many approaches to the problem of uncertain inference, ranging from probability to inductive logic to nonmonotonic logic. Thisbook seeks to provide a clear exposition of these approaches within a unified framework. The principal market for the book (...) will be students and professionals in philosophy, computer science, and AI. Among the special features of the book are a chapter on evidential probability, which has not received a basic exposition before; chapters on nonmonotonic reasoning and theory replacement, matters rarely addressed in standard philosophical texts; and chapters on Mill's methods and statistical inference that cover material sorely lacking in the usual treatments of AI and computer science. (shrink)

In this work Henry Kyburg presents his views on a wide range of philosophical problems associated with the study and practice of science and mathematics. The main structure of the book consists of a presentation of Kyburg's notions of epistemic probability and its use in the scientific enterprise i.e., the effort to modify previously adopted beliefs in the light of experience. Intended for cognitive scientists and people in artificial intelligence as well as for technically oriented philosophers, the book also provides (...) a general overview of the philosophy of science for the non-philosopher by one of the leading authorities in the field. (shrink)

People have worried for many years — centuries — about how you perform large changes in your body of beliefs. How does the new evidence lead you to replace a geocentric system of planetary motion by a heliocentric system? How do we decide to abandon the principle of the conservation of mass?The general approach that we will try to defend here is that an assumption, presupposition, framework principle, will be rejected or altered when a large enough number of improbabilities must (...) be accepted on be basis of our experience. If I think that all swans are white, and a student claims to have a counterexample, I will assume that he has made some observational error. I will reject his result, and continue to accept the generalization. When a lot of people claim to have seen counterexamples, I will come around: to continue to accept the generalization would require me to accept too many improbabilities. (shrink)

Ralph Waldo Emerson said, “a Foolish consistency is the hobgoblin of little minds, adored by little statesmen and philosophers and divines.” The alleged evidence has mounted that ordinary folk are prone to inconsistency, and particularly that they are prone to inconsistency when it comes to probabilistic judgments. I write “alleged,” because it is open to question whether the experiments that provide this evidence are well designed—in particular whether Quine’s principle of logistical charity has been followed. I also do so because (...) in some cases of probability judgments the untutored intuitions of ordinary people seem to be at least as good as, and perhaps better than, the intuitions of those who run the experiments. (shrink)

Ralph Waldo Emerson said, “a Foolish consistency is the hobgoblin of little minds, adored by little statesmen and philosophers and divines.” The alleged evidence has mounted that ordinary folk are prone to inconsistency, and particularly that they are prone to inconsistency when it comes to probabilistic judgments. I write “alleged,” because it is open to question whether the experiments that provide this evidence are well designed—in particular whether Quine’s principle of logistical charity has been followed. I also do so because (...) in some cases of probability judgments the untutored intuitions of ordinary people seem to be at least as good as, and perhaps better than, the intuitions of those who run the experiments. (shrink)

If someone comes to my house, saying, "Here is a bone; I hope Obrecht likes it," I might answer with a deductive argument: "You may rest assured on that score. Obrecht is a dog, and all dogs like bones; therefore Obrecht will like it." We may formalize this argument as follows: Let G be the bone, O be Obrecht, D be the class of dogs, B be the class of bones, and, finally, let L be the class of ordered pairs (...) such that x likes y. The premises are then: x ∈ D ⋅ y ∈ B ⋅ ⊃ ∈ L) G ∈ B O ∈ D. (shrink)

These essays are characterized by meticulous argument in the analytical tradition. The book concerns matters of metaphysics in a broad sense: philosophy of mind and the problems of subjectivity; questions concerning nomological and statistical laws of nature; and, as we would expect, chance and induction.