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Reactive Search and Intelligent Optimization

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Cover of 'Reactive Search and Intelligent Optimization'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction: Machine Learning for Intelligent Optimization
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    Chapter 2 Reacting on the neighborhood
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    Chapter 3 Reacting on the Annealing Schedule
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    Chapter 4 Reactive Prohibitions
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    Chapter 5 Reacting on the Objective Function
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    Chapter 6 Reacting on the Objective Function
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    Chapter 7 Supervised Learning
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    Chapter 8 Reinforcement Learning
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    Chapter 9 Algorithm Portfolios and Restart Strategies
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    Chapter 10 Racing
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    Chapter 11 Teams of Interacting Solvers
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    Chapter 12 Metrics, Landscapes and Features
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    Chapter 13 Open Problems
Attention for Chapter 11: Teams of Interacting Solvers
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