Self-organizing coalitions for managing complexity : agent-based simulation of evolutionary game theory models using dynamic social networks for interdisciplinary applications
Author(s)
Bibliographic Information
Self-organizing coalitions for managing complexity : agent-based simulation of evolutionary game theory models using dynamic social networks for interdisciplinary applications
（Emergence, complexity and computation / series editors Ivan Zelinka, Andrew Adamatzky, Guanrong Chen, 29）
Springer, c2018
- : pbk
Available at / 1 libraries
-
No Libraries matched.
- Remove all filters.
Note
Includes bibliographical references and index
Softcover reprint of the hardcover 1st edition 2017
Description and Table of Contents
Description
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.
Table of Contents
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.
by "Nielsen BookData"
