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- Author: John L Pollock
- Publisher: Oxford University Press, USA
- ISBN-10: 019506013X
- ISBN-13: 9780195060133
- Format: 14.9 x 22.6 x 2.8 cm, hardcover
- Language: English
- SAVE -10% with code: EXTRA
Nomic Probability and the Foundations of Induction (e-book) (used book) | bookbook.eu
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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.
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- Author: John L Pollock
- Publisher: Oxford University Press, USA
- ISBN-10: 019506013X
- ISBN-13: 9780195060133
- Format: 14.9 x 22.6 x 2.8 cm, hardcover
- Language: English English
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.
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