This book presents a major conceptual and speculative philosophic investigation of knowledge, belief, and decision. It offers a distinctive approach to the improvement of knowledge where knowledge is construed as a resource for deliberation and inquiry. The first three chapters of the book address the question of the revision of knowledge from a highly original point of view, one that takes issue with the fallibilist doctrines of Peirce and Popper, and with the views of Dewey, Quine, and Kuhn as well. The next ten chapters are more technical in nature but require relatively little background in mathematical technique. Among the topics discussed are inductive logic and inductive probability, utility theory, rational decision making, value conflict, chance (statistical probability), direct inference, and inverse inference. Chapters 14-17 review alternative approaches to the topic of inverse statistical inference. Much of the discussion focuses on contrasting Bayesian and anti-Bayesian reactions to R. A. Fisher's fiducial argument. This section of the book concludes with a discussion of the Neyman-Pearson-Wald approach to the foundations of statistical inference. The final chapter returns to the epistemological themes with which the book opened, emphasizing the question of the objectivity of human inquiry. An appendix provides a real-world application of Levi's theories of knowledge and probability, offering a critique of some of the methodological procedures employed in the Rasmussen Report to assess risks of major accidents in nuclear power plants. There are also references and an index. The Enterprise of Knowledgewill interest professionals and students in epistemology, philosophy of science, decision theory, probability theory, and statistical inference.
Description:
This book presents a major conceptual and speculative philosophic investigation of knowledge, belief, and decision. It offers a distinctive approach to the improvement of knowledge where knowledge is construed as a resource for deliberation and inquiry. The first three chapters of the book address the question of the revision of knowledge from a highly original point of view, one that takes issue with the fallibilist doctrines of Peirce and Popper, and with the views of Dewey, Quine, and Kuhn as well. The next ten chapters are more technical in nature but require relatively little background in mathematical technique. Among the topics discussed are inductive logic and inductive probability, utility theory, rational decision making, value conflict, chance (statistical probability), direct inference, and inverse inference. Chapters 14-17 review alternative approaches to the topic of inverse statistical inference. Much of the discussion focuses on contrasting Bayesian and anti-Bayesian reactions to R. A. Fisher's fiducial argument. This section of the book concludes with a discussion of the Neyman-Pearson-Wald approach to the foundations of statistical inference. The final chapter returns to the epistemological themes with which the book opened, emphasizing the question of the objectivity of human inquiry. An appendix provides a real-world application of Levi's theories of knowledge and probability, offering a critique of some of the methodological procedures employed in the Rasmussen Report to assess risks of major accidents in nuclear power plants. There are also references and an index. The Enterprise of Knowledgewill interest professionals and students in epistemology, philosophy of science, decision theory, probability theory, and statistical inference.