Networks, Games, and Dynamics
From Dynamical Systems and Stochastic Analysis to Transportation Theory and Optimal Control
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Beschreibung
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 emcompasses 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 in 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 practicioners and anyone interested in exploring the interplay among these fields.
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.
Covers theory and applications in dynamical systems, stochastic analysis, optimization, and more Focuses on the interplay between research fields to address real-world problems Gathers cutting-edge research from renowned experts
Autor*in
Mansoor Saburov
Themen in »Networks, Games, and Dynamics«
conference proceedings differential equations dynamical systems computing control and optimization functional analysis nonlinear analysis harmonic analysis approximation operator theory mathematical physics biomathematics mathematical finance machine learning stochastic analysis