Self-organizing Coalitions for Managing Complexity
Agent-based Simulation of Evolutionary Game Theory Models using Dynamic Social Networks for Interdisciplinary Applications
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Beschreibung
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.
Presents self-organizing coalitions and their applications in multiple areas of complex systems Includes a basic introduction to game theory, multi-agent systems, complex systems, cellular automata, and self-organization Addresses the use of coalitions and evolutionary game theory for optimization using cellular automata models, and for prediction using neural networks Offers several experimental models related to self-organization
Autor*in
Juan C. Burguillo
Themen in »Self-organizing Coalitions for Managing Complexity«
Coalitions Complexity Modeling Evolutionary Computation Evolutionary Game Theory Multi-agent Systems Optimization Prediction Self-organization complexity