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There are many proposed aims for scientific inquiry - to explain or predict events, to confirm or falsify hypotheses, or to find hypotheses that cohere with our other beliefs in some logical or probabilistic sense. This book is devoted to a different proposal - that the logical structure of the scientist's method should guarantee eventual arrival at the truth, given the scientist's background assumptions. Interest in this methodological property, called "logical reliability," stems from formal learning theory, which draws its insights not from the theory of probability, but from the theory of computability. Kelly first offers an accessible explanation of formal learning theory, then goes on to develop and explore a systematic framework in which various standard learning-theoretic results can be seen as special cases of simpler and more general considerations. Finally, Kelly clarifies the relationship between the resulting framework and other standard issues in the philosophy of science, such as probability, causation, and relativism. Extensively illustrated with figures by the author, The Logic of Reliable Inquiry assumes only introductory knowledge of basic logic and computability theory. It is a major contribution to the literature and will be essential reading for scientists, statiticians, psychologists, linguists, logicians, and philosophers.
This book investigates whether the logical structure of scientific methodology can guarantee the eventual attainment of truth based on established background assumptions. Kevin T. Kelly, a scholar in the field of formal learning theory, utilizes the principles of computability theory rather than traditional probability to construct his argument. He presents a systematic framework that organizes various learning-theoretic results into a unified structure, providing a rigorous foundation for understanding how inquiry functions. By bridging the gap between formal logic and the philosophy of science, the author offers a new perspective on how scientists can reliably reach accurate conclusions.
What You Will Find
Experts recognize this work as a significant contribution to the intersection of philosophy and formal logic, particularly for its departure from standard probabilistic models. Readers frequently note that while the text assumes introductory knowledge of logic and computability, it remains a foundational resource for researchers across disciplines including statistics, linguistics, and psychology.
Page Count:
0
Publication Date:
1900-01-01
Publisher:
Oxford University Press, USA
ISBN-10:
0195091965
ISBN-13:
9780195091960
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