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
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
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.
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.
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.
Inhaltsverzeichnis
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.
Klappentext
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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