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Selforganizing Coalitions For Managing Complexity Agentbased Simulation Of Evolutionary Game Theory Models Using Dynamic Social Networks For Interdisciplinary Applications 1st Edition Juan C Burguillo Auth

  • SKU: BELL-6842308
Selforganizing Coalitions For Managing Complexity Agentbased Simulation Of Evolutionary Game Theory Models Using Dynamic Social Networks For Interdisciplinary Applications 1st Edition Juan C Burguillo Auth
$ 31.00 $ 45.00 (-31%)

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Selforganizing Coalitions For Managing Complexity Agentbased Simulation Of Evolutionary Game Theory Models Using Dynamic Social Networks For Interdisciplinary Applications 1st Edition Juan C Burguillo Auth instant download after payment.

Publisher: Springer International Publishing
File Extension: PDF
File size: 24.9 MB
Pages: 348
Author: Juan C. Burguillo (auth.)
ISBN: 9783319698960, 9783319698984, 3319698966, 3319698982
Language: English
Year: 2018
Edition: 1

Product desciption

Selforganizing Coalitions For Managing Complexity Agentbased Simulation Of Evolutionary Game Theory Models Using Dynamic Social Networks For Interdisciplinary Applications 1st Edition Juan C Burguillo Auth by Juan C. Burguillo (auth.) 9783319698960, 9783319698984, 3319698966, 3319698982 instant download after payment.

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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