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Self-organizing Coalitions for Managing Complexity [electronic resource] : Agent-based Simulation of Evolutionary Game Theory Models using Dynamic Social Networks for Interdisciplinary Applications / by Juan C. Burguillo.

By: Burguillo, Juan C [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Emergence, Complexity and Computation: 29Publisher: Cham : Springer International Publishing : Imprint: Springer, 2018Edition: 1st ed. 2018.Description: XVI, 343 p. 187 illus., 149 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319698984.Subject(s): Dynamics | Nonlinear theories | Computational intelligence | Operations research | Graph theory | Applied Dynamical Systems | Computational Intelligence | Operations Research and Decision Theory | Graph TheoryAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 515.39 Online resources: Click here to access online
Contents:
Introduction.- Complex Systems -- Complex Networks.- Cellular Automata.- Multi-agent Systems -- Self-Organization.- Game Theory.- Optimization Models with Coalitional Cellular Automata -- Time Series Prediction using Coalitions and Self-Organizing Maps.
In: Springer Nature eBookSummary: This book provides an interdisciplinary approach to complexity, combining ideas from areas like complex networks, cellular automata, multi-agent systems, self-organization and game theory. The first part of the book provides an extensive introduction to these areas, while the second explores a range of research scenarios. Lastly, the book presents CellNet, a software framework that offers a hands-on approach to the scenarios described throughout the book. In light of the introductory chapters, the research chapters, and the CellNet simulating framework, this book can be used to teach undergraduate and master’s students in disciplines like artificial intelligence, computer science, applied mathematics, economics and engineering. Moreover, the book will be particularly interesting for Ph.D. and postdoctoral researchers seeking a general perspective on how to design and create their own models.
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Introduction.- Complex Systems -- Complex Networks.- Cellular Automata.- Multi-agent Systems -- Self-Organization.- Game Theory.- Optimization Models with Coalitional Cellular Automata -- Time Series Prediction using Coalitions and Self-Organizing Maps.

This book provides an interdisciplinary approach to complexity, combining ideas from areas like complex networks, cellular automata, multi-agent systems, self-organization and game theory. The first part of the book provides an extensive introduction to these areas, while the second explores a range of research scenarios. Lastly, the book presents CellNet, a software framework that offers a hands-on approach to the scenarios described throughout the book. In light of the introductory chapters, the research chapters, and the CellNet simulating framework, this book can be used to teach undergraduate and master’s students in disciplines like artificial intelligence, computer science, applied mathematics, economics and engineering. Moreover, the book will be particularly interesting for Ph.D. and postdoctoral researchers seeking a general perspective on how to design and create their own models.

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