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Foundations of Knowledge Acquisition

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Cover of 'Foundations of Knowledge Acquisition'

Table of Contents

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    Book Overview
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    Chapter 1 Learning = Inferencing + Memorizing
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    Chapter 2 Adaptive Inference
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    Chapter 3 On Integrating Machine Learning with Planning
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    Chapter 4 The Role of Self-Models in Learning to Plan
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    Chapter 5 Learning Flexible Concepts Using a Two-Tiered Representation
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    Chapter 6 Competition-Based Learning
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    Chapter 7 Problem Solving via Analogical Retrieval and Analogical Search Control
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    Chapter 8 A View of Computational Learning Theory
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    Chapter 9 The Probably Approximately Correct (PAC) and Other Learning Models
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    Chapter 10 On the Automated Discovery of Scientific Theories
Attention for Chapter 5: Learning Flexible Concepts Using a Two-Tiered Representation
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