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Oppositional Concepts in Computational Intelligence

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Cover of 'Oppositional Concepts in Computational Intelligence'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Opposition-Based Computing
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    Chapter 3 Antithetic and Negatively Associated Random Variables and Function Maximization
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    Chapter 4 Opposition and Circularity
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    Chapter 5 Collaborative vs. Conflicting Learning, Evolution and Argumentation
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    Chapter 6 Proof-Number Search and Its Variants
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    Chapter 7 Improving the Exploration Ability of Ant-Based Algorithms
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    Chapter 8 Differential Evolution Via Exploiting Opposite Populations
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    Chapter 9 Evolving Opposition-Based Pareto Solutions: Multiobjective Optimization Using Competitive Coevolution
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    Chapter 10 Bayesian Ying-Yang Harmony Learning for Local Factor Analysis: A Comparative Investigation
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    Chapter 11 The Concept of Opposition and Its Use in Q -Learning and Q ( λ ) Techniques
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    Chapter 12 Two Frameworks for Improving Gradient-Based Learning Algorithms
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    Chapter 13 Opposite Actions in Reinforced Image Segmentation
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    Chapter 14 Opposition Mining in Reservoir Management
Attention for Chapter 4: Opposition and Circularity
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Chapter title
Opposition and Circularity
Chapter number 4
Book title
Oppositional Concepts in Computational Intelligence
Published by
Springer, Berlin, Heidelberg, January 2008
DOI 10.1007/978-3-540-70829-2_4
Book ISBNs
978-3-54-070826-1, 978-3-54-070829-2
Authors

Florencio G. Asenjo

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