Buch, Englisch, Band 29, 343 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 546 g
Self-organizing Coalitions for Managing Complexity
Softcover Nachdruck of the original 1. Auflage 2018
ISBN: 978-3-319-88859-0
Verlag: Springer International Publishing
Agent-based Simulation of Evolutionary Game Theory Models using Dynamic Social Networks for Interdisciplinary Applications
Buch, Englisch, Band 29, 343 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 546 g
Reihe: Emergence, Complexity and Computation
ISBN: 978-3-319-88859-0
Verlag: Springer International Publishing
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Naturwissenschaften Physik Angewandte Physik Statistische Physik, Dynamische Systeme
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
- Mathematik | Informatik EDV | Informatik Informatik Berechenbarkeitstheorie, Komplexitätstheorie
Weitere Infos & Material
Introduction.- Complex Systems.- Complex Networks.- Cellular Automata.- Multi-agent Systems.- Self-Organization.- Game Theory.- Optimization Models with Coalitional CellularAutomata.- Time Series Prediction using Coalitions and Self-Organizing Maps.