This book deals with the subject of probabilistic reasoning. Professor Pollock attempts to make general philosophical sense of objective probabilities and he explores their relationship to the problem of induction. He argues that probability is fundamental not only to physical science, but to induction, epistemology, the philosophy of science and to much reasoning of interest to artificial intelligence. He attempts to show how his understanding of probability throws light on these related issues.
Pollock's main claim is that the fundamental notion of probability is nomic - that is, it involves the notion of natural law, valid across possible worlds. The various epistemic and statistical conceptions of probability, he demonstrates, are derived from this nomic notion. He goes on to provide a theory of statistical induction; an account of computational principles allowing some probabilities to be derived from others; an account of acceptance rules; and a theory of direct inference.
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21,5 x 14,5 cm. Zustand: Gut. XVIII, 344 Pages ; With Figures Original Halbleinen Einband mit Bibliotheksschild auf Vorderdeckel. Innen mit Bibliotheksstempeln, sauberer, sehr guter Zustand. Englische Sprache. - Original Half Cloth Binding with Library label on front cover. Inside with Library stamps, in very good condition. English Language B12-03-04F|S28 Sprache: Englisch Gewicht in Gramm: 486. Artikel-Nr. 56235
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 368 | Sprache: Englisch | Produktart: Bücher | In this book Pollock deals with the subject of probabilistic reasoning, making general philosophical sense of objective probabilities and exploring their relationship to the problem of induction. He argues that probability is fundamental not only to physical science, but to induction, epistemology, the philosophy of science and much of the reasoning relevant to artificial intelligence. Pollock's main claim is that the fundamental notion of probability is nomic--that is, it involves the notion of natural law, valid across possible worlds. The various epistemic and statistical conceptions of probability, he demonstrates, are derived from this nomic notion. He goes on to provide a theory of statistical induction, an account of computational principles allowing some probabilities to be derived from others, an account of acceptance rules, and a theory of direct inference. Artikel-Nr. 2081384/2
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