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Guided Self-Organization: Inception

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Cover of 'Guided Self-Organization: Inception'

Table of Contents

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    Book Overview
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    Chapter 1 On the Cross-Disciplinary Nature of Guided Self-Organisation
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    Chapter 2 Information Measures of Complexity, Emergence, Self-organization, Homeostasis, and Autopoiesis
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    Chapter 3 Generating Functionals for Guided Self-Organization
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    Chapter 4 Empowerment–An Introduction
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    Chapter 5 A Framework for the Local Information Dynamics of Distributed Computation in Complex Systems
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    Chapter 6 Quantifying Synergistic Mutual Information
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    Chapter 7 On the Role of Embodiment for Self-Organizing Robots: Behavior As Broken Symmetry
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    Chapter 8 Robot Learning by Guided Self-Organization
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    Chapter 9 On the Causal Structure of the Sensorimotor Loop
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    Chapter 10 Action Switching in Brain-Body-Environment Systems
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    Chapter 11 Guided Self-Organization of Input-Driven Recurrent Neural Networks
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    Chapter 12 Measuring Information Dynamics in Swarms
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    Chapter 13 Guiding Designs of Self-Organizing Swarms: Interactive and Automated Approaches
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    Chapter 14 Mutual Information As a Task-Independent Utility Function for Evolutionary Robotics
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    Chapter 15 Evolution of Complexity and Neural Topologies
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    Chapter 16 Clustering and Modularity in Self-Organized Networks
Attention for Chapter 14: Mutual Information As a Task-Independent Utility Function for Evolutionary Robotics
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Citations

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Chapter title
Mutual Information As a Task-Independent Utility Function for Evolutionary Robotics
Chapter number 14
Book title
Guided Self-Organization: Inception
Published by
Springer, Berlin, Heidelberg, January 2014
DOI 10.1007/978-3-642-53734-9_14
Book ISBNs
978-3-64-253733-2, 978-3-64-253734-9
Authors

Valerio Sperati, Vito Trianni, Stefano Nolfi

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 33%
Researcher 2 33%
Professor 1 17%
Unknown 1 17%
Readers by discipline Count As %
Engineering 3 50%
Computer Science 2 33%
Unknown 1 17%

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