This contributed volume provides an integrated perspective on modern mathematical and computational techniques for addressing complex problems in networks, control systems, learning, and game theory. It encompasses state-of-the-art research from a diverse range of disciplines, including dynamical systems, stochastic analysis, optimization, game theory, machine learning, and transportation theory. Particular emphasis is placed on connecting rigorous theoretical developments with real-world applications.
This volume is organized into twelve chapters. The first part (Chapters 1-6) addresses the optimal transportation problem in traffic networks. The second part (Chapters 7-11) investigates Markov chains with memory by examining the geometric, algebraic, dynamical, and ergodic properties of quadratic (polynomial) stochastic operators associated with cubic stochastic hypermatrices. Finally, Chapter 12 illustrates how methods from stochastic analysis and dynamical systems can be applied to lattice models of statistical mechanics defined on a Cayley tree.
Intended to serve as a comprehensive reference for academics and researchers, this volume may also benefit practitioners and anyone interested in exploring the interplay among these fields.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Mansoor Saburov is an Associate Professor at the Gulf University for Science and Technology. He received his PhD in Mathematics (2011) from the International Islamic University Malasia. His research interests lie in dynamical systems, functional analysis, quantum probability, and (p)-adic analysis.
Naira Hovakimyan is a Professor at the University of Illinois at Urbana-Champaign, USA. She received her PhD in Physics and Mathematics (1992) from the Institute of Applied Mathematics of the Russian Academy of Sciences. Her research interests include control and optimization, autonomous systems, machine learning, neural networks, and their applications.
Armen Badgasaryan is Researcher at the Institute of Mathematics of the National Academy of Sciences, Armenia, and Associate Professor at the Institute of Mathematics and Informatics of Russian-Armenian University, Armenia. He holds a Ph.D. in applied mathematics (2000) from the Russian Academy of Sciences. He does research in the fields of number theory, analysis, dynamical systems, optimization and control, and optimal transport.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This contributed volume provides an integrated perspective on modern mathematical and computational techniques for addressing complex problems in networks, control systems, learning, and game theory. It encompasses state-of-the-art research from a diverse range of disciplines, including dynamical systems, stochastic analysis, optimization, game theory, machine learning, and transportation theory. Particular emphasis is placed on connecting rigorous theoretical developments with real-world applications.This volume is organized into twelve chapters. The first part (Chapters 1-6) addresses the optimal transportation problem in traffic networks. The second part (Chapters 7-11) investigates Markov chains with memory by examining the geometric, algebraic, dynamical, and ergodic properties of quadratic (polynomial) stochastic operators associated with cubic stochastic hypermatrices. Finally, Chapter 12 illustrates how methods from stochastic analysis and dynamical systems can be applied to lattice models of statistical mechanics defined on a Cayley tree.Intended to serve as a comprehensive reference for academics and researchers, this volume may also benefit practitioners and anyone interested in exploring the interplay among these fields. 308 pp. Englisch. N° de réf. du vendeur 9783032091758
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Buch. Etat : Neu. Networks, Games, and Dynamics | From Dynamical Systems and Stochastic Analysis to Transportation Theory and Optimal Control | Mansoor Saburov (u. a.) | Buch | Trends in Mathematics | viii | Englisch | 2025 | Springer | EAN 9783032091758 | Verantwortliche Person für die EU: Springer Basel AG in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. N° de réf. du vendeur 134413223
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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This contributed volume provides an integrated perspective on modern mathematical and computational techniques for addressing complex problems in networks, control systems, learning, and game theory. It encompasses state-of-the-art research from a diverse range of disciplines, including dynamical systems, stochastic analysis, optimization, game theory, machine learning, and transportation theory. Particular emphasis is placed on connecting rigorous theoretical developments with real-world applications.This volume is organized into twelve chapters. The first part (Chapters 1-6) addresses the optimal transportation problem in traffic networks. The second part (Chapters 7-11) investigates Markov chains with memory by examining the geometric, algebraic, dynamical, and ergodic properties of quadratic (polynomial) stochastic operators associated with cubic stochastic hypermatrices. Finally, Chapter 12 illustrates how methods from stochastic analysis and dynamical systems can be applied to lattice models of statistical mechanics defined on a Cayley tree.Intended to serve as a comprehensive reference for academics and researchers, this volume may also benefit practitioners and anyone interested in exploring the interplay among these fields.Springer Nature c/o IBS, Benzstrasse 21, 48619 Heek 316 pp. Englisch. N° de réf. du vendeur 9783032091758
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This contributed volume provides an integrated perspective on modern mathematical and computational techniques for addressing complex problems in networks, control systems, learning, and game theory. It encompasses state-of-the-art research from a diverse range of disciplines, including dynamical systems, stochastic analysis, optimization, game theory, machine learning, and transportation theory. Particular emphasis is placed on connecting rigorous theoretical developments with real-world applications.This volume is organized into twelve chapters. The first part (Chapters 1-6) addresses the optimal transportation problem in traffic networks. The second part (Chapters 7-11) investigates Markov chains with memory by examining the geometric, algebraic, dynamical, and ergodic properties of quadratic (polynomial) stochastic operators associated with cubic stochastic hypermatrices. Finally, Chapter 12 illustrates how methods from stochastic analysis and dynamical systems can be applied to lattice models of statistical mechanics defined on a Cayley tree.Intended to serve as a comprehensive reference for academics and researchers, this volume may also benefit practitioners and anyone interested in exploring the interplay among these fields. N° de réf. du vendeur 9783032091758
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