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Induction, Algorithmic Learning Theory, and Philosophy

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Cover of 'Induction, Algorithmic Learning Theory, and Philosophy'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to the Philosophy and Mathematics of Algorithmic Learning Theory
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    Chapter 2 Inductive Inference Systems for Learning Classes of Algorithmically Generated Sets and Structures
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    Chapter 3 Deduction, Induction, and beyond in Parametric Logic
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    Chapter 4 How Simplicity Helps You Find the Truth without Pointing at it
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    Chapter 5 Induction over the Continuum
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    Chapter 6 Logically Reliable Inductive Inference
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    Chapter 7 Some Philosophical Concerns about the Confidence in ‘Confident Learning’
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    Chapter 8 How to Do Things with an Infinite Regress
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    Chapter 9 Trade-Offs
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    Chapter 10 Two Ways of Thinking about Induction
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    Chapter 11 Between History and Logic
Attention for Chapter 9: Trade-Offs
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Chapter title
Trade-Offs
Chapter number 9
Book title
Induction, Algorithmic Learning Theory, and Philosophy
Published by
Springer, Dordrecht, January 2007
DOI 10.1007/978-1-4020-6127-1_9
Book ISBNs
978-1-4020-6126-4, 978-1-4020-6127-1
Authors

Clark Glymour

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