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Induction, Algorithmic Learning Theory, and Philosophy
ISBN-13:
9781402061271
Veröffentl:
2007
Seiten:
290
Autor:
Michèle Friend
Serie:
9, Logic, Epistemology, and the Unity of Science
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
1 - PDF Watermark
Sprache:
Englisch
Beschreibung:
This is the first book to collect essays from philosophers, mathematicians and computer scientists working at the exciting interface of algorithmic learning theory and the epistemology of science and inductive inference. Readable, introductory essays provide engaging surveys of different, complementary, and mutually inspiring approaches to the topic, both from a philosophical and a mathematical viewpoint.
"This is the first book to collect essays from philosophers, mathematicians and computer scientists working at the exciting interface of algorithmic learning theory and the epistemology of science and inductive inference. Readable, introductory essays provide engaging surveys of different, complementary, and mutually inspiring approaches to the topic, both from a philosophical and a mathematical viewpoint.
to the Philosophy and Mathematics of Algorithmic Learning Theory.- to the Philosophy and Mathematics of Algorithmic Learning Theory.- Technical Papers.- Inductive Inference Systems for Learning Classes of Algorithmically Generated Sets and Structures.- Deduction, Induction, and beyond in Parametric Logic.- How Simplicity Helps You Find the Truth without Pointing at it.- Induction over the Continuum.- Philosophy Papers.- Logically Reliable Inductive Inference.- Some Philosophical Concerns about the Confidence in 'Confident Learning'.- How to Do Things with an Infinite Regress.- Trade-Offs.- Two Ways of Thinking about Induction.- Between History and Logic.
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