Generalized Nash Equilibrium Seeking in Population Games: Applications in the Control of Large-Scale Multi-agent Systems
About this ebook
The book is structured to guide readers from foundational concepts such as variational inequalities and dissipativity theory, to advanced topics like the design of evolutionary and payoff dynamics models for distributed systems. The clear progression from theory to application is enhanced by numerous hands-on examples and fully documented Python code allowing readers to replicate and customize the book’s simulations for deeper understanding. Features of the text include:
- detailed illustrations of theoretical concepts,
- solutions to practical problems and
- a unique focus on integrating game theory with optimization-based control.
This blend of rigorous theory and practical application makes this book a valuable resource for both students and professionals in the field of control systems and multi-agent decision-making.
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About the author
Doctor Juan Martinez-Piazuelo has made notable contributions to the research and development of optimization-based control strategies for large-scale complex systems using game-theoretical approaches. His expertise spans evolutionary game theory, generalized Nash equilibrium problems, and distributed optimization, all focused on large-scale, non-cooperative multi-agent systems with real-world applications. His research has been widely published in high-impact scientific journals and presented at prestigious international conferences.
Professor Carlos Ocampo-Martinez has been deeply engaged in research and development in the management and control of large-scale complex systems, particularly in the domains of water and energy. His work spans evolutionary game theory, model predictive control, and distributed optimization techniques for managing complex networks. With a strong focus on real-world applications, he has published over a hundred of high-impact journal articles, covering topics such as decentralized control for urban water and energy systems, predictive control of complex networks, and the management of clean energy production. Additionally, he has authored and edited several influential books with Springer, focusing on advanced control strategies for large-scale systems.
Professor Nicanor Quijano is an expert in the modeling and control of distributed network optimization systems, particularly those that are utilized in the fields of agriculture, energy, and urban drainage systems. His research has mostly concentrated on topics such as real-time management of urban drainage and irrigation systems, dynamic population games for optimal dispatch in hierarchical microgrid control, and the dispatch of distributed generators employing population dynamics. His knowledge in these areas provides relevant insights into the issues and solutions connected with integrating energy vectors as well as the water-energy-food nexus, which is paramount in this sort of research problem. His work has been published in a number of peer-reviewed journals.
