Networked control systems are increasingly ubiquitous today, with applications ranging from vehicle communication and adaptive power grids to space exploration and economics. The optimal design of such systems presents major challenges, requiring tools from various disciplines within applied mathematics such as decentralized control, stochastic control, information theory, and quantization.

A thorough, self-contained book, "Stochastic Networked Control Systems: Stabilization and Optimization under Information Constraints" aims to connect these diverse disciplines with precision and rigor, while conveying design guidelines to controller architects. Unique in the literature, it lays a comprehensive theoretical foundation for the study of networked control systems, and introduces an array of concrete tools for work in the field. Salient features included:

. Characterization, comparison and optimal design of information structures in static and dynamic teams. Operational, structural and topological properties of information structures in optimal decision making, with a systematic program for generating optimal encoding and control policies. The notion of signaling, and its utilization in stabilization and optimization of decentralized control systems.

. Presentation of mathematical methods for stochastic stability of networked control systems using random-time, state-dependent drift conditions and martingale methods.

. Characterization and study of information channels leading to various forms of stochastic stability such as stationarity, ergodicity, and quadratic stability; and connections with information and quantization theories. Analysis of various classes of centralized and decentralized control systems.

. Jointly optimal design of encoding and control policies over various information channels and under general optimization criteria, including a detailed coverage of linear-quadratic-Gaussian models.

. Decentralized agreement and dynamic optimization under information constraints.

This monograph is geared toward a broad audience of academic and industrial researchers interested in control theory, information theory, optimization, economics, and applied mathematics. It could likewise serve as a supplemental graduate text. The reader is expected to have some familiarity with linear systems, stochastic processes, and Markov chains, but the necessary background can also be acquired in part through the four appendices included at the end.

. Characterization, comparison and optimal design of information structures in static and dynamic teams. Operational, structural and topological properties of information structures in optimal decision making, with a systematic program for generating optimal encoding and control policies. The notion of signaling, and its utilization in stabilization and optimization of decentralized control systems.

. Presentation of mathematical methods for stochastic stability of networked control systems using random-time, state-dependent drift conditions and martingale methods.

. Characterization and study of information channels leading to various forms of stochastic stability such as stationarity, ergodicity, and quadratic stability; and connections with information and quantization theories. Analysis of various classes of centralized and decentralized control systems.

. Jointly optimal design of encoding and control policies over various information channels and under general optimization criteria, including a detailed coverage of linear-quadratic-Gaussian models.

. Decentralized agreement and dynamic optimization under information constraints.

This monograph is geared toward a broad audience of academic and industrial researchers interested in control theory, information theory, optimization, economics, and applied mathematics. It could likewise serve as a supplemental graduate text. The reader is expected to have some familiarity with linear systems, stochastic processes, and Markov chains, but the necessary background can also be acquired in part through the four appendices included at the end.

The chapters in this volume, and the volume itself, celebrate the life and research of Roberto Tempo, a leader in the study of complex networked systems, their analysis and control under uncertainty, and robust designs. Contributors include authorities on uncertainty in systems, robustness, networked and network systems, social networks, distributed and randomized algorithms, and multi-agent systems-all fields that Roberto Tempo made vital contributions to. Additionally, at least one author of each chapter was a research collaborator of Roberto Tempo's. This volume is structured in three parts. The first covers robustness and includes topics like time-invariant uncertainties, robust static output feedback design, and the uncertainty quartet. The second part is focused on randomization and probabilistic methods, which covers topics such as compressive sensing, and stochastic optimization. Finally, the third part deals with distributed systems and algorithms, and explores matters involving mathematical sociology, fault diagnoses, and PageRank computation. Each chapter presents exposition, provides new results, and identifies fruitful future directions in research. This book will serve as a valuable reference volume to researchers interested in uncertainty, complexity, robustness, optimization, algorithms, and networked systems.

Recent years have witnessed a surge of activity in the field of dynamic both theory and applications. Theoretical as well as practical games, in problems in zero-sum and nonzero-sum games, continuous time differential and discrete time multistage games, and deterministic and stochastic games games are currently being investigated by researchers in diverse disciplines, such as engineering, mathematics, biology, economics, management science, and political science. This surge of interest has led to the formation of the International Society of Dynamic Games (ISDG) in 1990, whose primary goal is to foster the development of advanced research and applications in the field of game theory. One important activity of the Society is to organize biannually an international symposium which aims at bringing together all those who contribute to the development of this active field of applied science. In 1992 the symposium was organized in Grimentz, Switzerland, under the supervision of an international scientific committee and with the help of a local organizing committee based at University of Geneva. This book, which is the first volume in the new Series, Annals of the International Society of Dynamic Games (see the Preface to the Series), is based on presentations made at this symposium. It is however more than a book of proceedings for a conference. Every paper published in this volume has passed through a very selective refereeing process, as in an archival technical journal.

The 28 revised full papers presented together with 8 short papers were carefully reviewed and selected from 44 submissions.Among the topical areas covered were: use of game theory; control theory; and mechanism design for security and privacy; decision making for cybersecurity and security requirements engineering; security and privacy for the Internet-of-Things; cyber-physical systems; cloud computing; resilient control systems, and critical infrastructure; pricing; economic incentives; security investments, and cyber insurance for dependable and secure systems; risk assessment and security risk management; security and privacy of wireless and mobile communications, including user location privacy; sociotechnological and behavioral approaches to security; deceptive technologies in cybersecurity and privacy; empirical and experimental studies with game, control, or optimization theory-based analysis for security and privacy; and adversarial machine learning and crowdsourcing, and the role of artificial intelligence in system security.

Networked control systems are increasingly ubiquitous today, with applications ranging from vehicle communication and adaptive power grids to space exploration and economics. The optimal design of such systems presents major challenges, requiring tools from various disciplines within applied mathematics such as decentralized control, stochastic control, information theory, and quantization. A thorough, self-contained book, Stochastic Networked Control Systems: Stabilization and Optimization under Information Constraints aims to connect these diverse disciplines with precision and rigor, while conveying design guidelines to controller architects. Unique in the literature, it lays a comprehensive theoretical foundation for the study of networked control systems, and introduces an array of concrete tools for work in the field. Salient features included: * Characterization, comparison and optimal design of information structures in static and dynamic teams. Operational, structural and topological properties of information structures in optimal decision making, with a systematic program for generating optimal encoding and control policies. The notion of signaling, and its utilization in stabilization and optimization of decentralized control systems. * Presentation of mathematical methods for stochastic stability of networked control systems using random-time, state-dependent drift conditions and martingale methods. * Characterization and study of information channels leading to various forms of stochastic stability such as stationarity, ergodicity, and quadratic stability; and connections with information and quantization theories. Analysis of various classes of centralized and decentralized control systems. * Jointly optimal design of encoding and control policies over various information channels and under general optimization criteria, including a detailed coverage of linear-quadratic-Gaussian models. * Decentralized agreement and dynamic optimization under information constraints. This monograph is geared toward a broad audience of academic and industrial researchers interested in control theory, information theory, optimization, economics, and applied mathematics. It could likewise serve as a supplemental graduate text. The reader is expected to have some familiarity with linear systems, stochastic processes, and Markov chains, but the necessary background can also be acquired in part through the four appendices included at the end. * Characterization, comparison and optimal design of information structures in static and dynamic teams. Operational, structural and topological properties of information structures in optimal decision making, with a systematic program for generating optimal encoding and control policies. The notion of signaling, and its utilization in stabilization and optimization of decentralized control systems. * Presentation of mathematical methods for stochastic stability of networked control systems using random-time, state-dependent drift conditions and martingale methods. * Characterization and study of information channels leading to various forms of stochastic stability such as stationarity, ergodicity, and quadratic stability; and connections with information and quantization theories. Analysis of various classes of centralized and decentralized control systems. * Jointly optimal design of encoding and control policies over various information channels and under general optimization criteria, including a detailed coverage of linear-quadratic-Gaussian models. * Decentralized agreement and dynamic optimization under information constraints. This monograph is geared toward a broad audience of academic and industrial researchers interested in control theory, information theory, optimization, economics, and applied mathematics. It could likewise serve as a supplemental graduate text. The reader is expected to have some familiarity with linear systems, stochastic processes, and Markov chains, but the necessary background can also be acquired in part through the four appendices included at the end.

Recent years have witnessed a surge of activity in the field of dynamic both theory and applications. Theoretical as well as practical games, in problems in zero-sum and nonzero-sum games, continuous time differential and discrete time multistage games, and deterministic and stochastic games games are currently being investigated by researchers in diverse disciplines, such as engineering, mathematics, biology, economics, management science, and political science. This surge of interest has led to the formation of the International Society of Dynamic Games (ISDG) in 1990, whose primary goal is to foster the development of advanced research and applications in the field of game theory. One important activity of the Society is to organize biannually an international symposium which aims at bringing together all those who contribute to the development of this active field of applied science. In 1992 the symposium was organized in Grimentz, Switzerland, under the supervision of an international scientific committee and with the help of a local organizing committee based at University of Geneva. This book, which is the first volume in the new Series, Annals of the International Society of Dynamic Games (see the Preface to the Series), is based on presentations made at this symposium. It is however more than a book of proceedings for a conference. Every paper published in this volume has passed through a very selective refereeing process, as in an archival technical journal.

Covering attack detection, malware response, algorithm and mechanism design, privacy, and risk management, this comprehensive work applies unique quantitative models derived from decision, control, and game theories to understanding diverse network security problems. It provides the reader with a system-level theoretical understanding of network security, and is essential reading for researchers interested in a quantitative approach to key incentive and resource allocation issues in the field. It also provides practitioners with an analytical foundation that is useful for formalising decision-making processes in network security.

I believe that the authors have written a first-class book which can be used for a second or third year graduate level course in the subject... Researchers working in the area will certainly use the book as a standard reference... Given how well the book is written and organized, it is sure to become one of the major texts in the subject in the years to come, and it is highly recommended to both researchers working in the field, and those who want to learn about the subject. a SIAM Review (Review of the First Edition) This book is devoted to one of the fastest developing fields in modern control theory---the so-called 'H-infinity optimal control theory'... In the authors' opinion 'the theory is now at a stage where it can easily be incorporated into a second-level graduate course in a control curriculum'. It seems that this book justifies this claim. a Mathematical Reviews (Review of the First Edition) This work is a perfect and extensive research reference covering the state-space techniques for solving linear as well as nonlinear H-infinity control problems. a IEEE Transactions on Automatic Control (Review of the Second Edition)

This volume contains eleven articles which deal with different aspects of dynaoic and differential game theory and its applications in economic modeling and decision making. All but one of these were presented as invited papers in special sessions I organized at the 7th Annual Conference on Economic Dynamics and Control in London, England, during the period June 26-28, 1985. The first article, which comprises Chapter 1, provides a general introduction to the topic of dynamic and differential game theory, discusses various noncooperative equilibrium solution concepts, includ ing Nash, Stackelberg, and Consistent Conjectural Variations equilibria, and a number of issues such as feedback and time-consistency. The second chapter deals with the role of information in Nash equilibria and the role of leadership in Stackelberg problems. A special type of a Stackelberg problem is the one in which one dominant player (leader) acquires dynamic information involving the actions of the others (followers), and constructs policies (so-called incentives) which enforce a certain type of behavior on the followers; Chapter 3 deals with such a class of problems and presents some new theoretical results on the existence of affine incentive policies. The topic of Chapter 4 is the computation of equilibria in discounted stochastic dynamic games. Here, for problems with finite state and decision spaces, existing algorithms are reviewed, with a comparative study of their speeds of convergence, and a new algorithm for the computation of nonzero-sum game equilibria is presented."

This unified treatment of game theory focuses on finding state-of-the-art solutions to issues surrounding the next generation of wireless and communications networks. Future networks will rely on autonomous and distributed architectures to improve the efficiency and flexibility of mobile applications, and game theory provides the ideal framework for designing efficient and robust distributed algorithms. This book enables readers to develop a solid understanding of game theory, its applications and its use as an effective tool for addressing wireless communication and networking problems. The key results and tools of game theory are covered, as are various real-world technologies including 3G networks, wireless LANs, sensor networks, dynamic spectrum access and cognitive networks. The book also covers a wide range of techniques for modeling, designing and analysing communication networks using game theory, as well as state-of-the-art distributed design techniques. This is an ideal resource for communications engineers, researchers, and graduate and undergraduate students.

Discover the very latest game-theoretic approaches for designing, modeling, and optimizing emerging wireless communication networks and systems with this unique text. Providing a unified and comprehensive treatment throughout, it explains basic concepts and theories for designing novel distributed wireless networking mechanisms, describes emerging game-theoretic tools from an engineering perspective, and provides an extensive overview of recent applications. A wealth of new tools is covered - including matching theory and games with bounded rationality - and tutorial chapters show how to use these tools to solve current and future wireless networking problems in areas such as 5G networks, network virtualization, software defined networks, cloud computing, the Internet of Things, context-aware networks, green communications, and security. This is an ideal resource for telecommunications engineers, and researchers in industry and academia who are working on the design of efficient, scalable, and robust communication protocols for future wireless networks, as well as graduate students in these fields.

Recent interest in biological games and mathematical finance make this classic 1982 text a necessity once again. Unlike other books in the field, this text provides an overview of the analysis of dynamic/differential zero-sum and nonzero-sum games and simultaneously stresses the role of different information patterns. The first edition was fully revised in 1995, adding new topics such as randomized strategies, finite games with integrated decisions, and refinements of Nash equilibrium. Readers can now look forward to even more recent results in this unabridged, revised SIAM Classics edition. Topics covered include static and dynamic noncooperative game theory, with an emphasis on the interplay between dynamic information patterns and structural properties of several different types of equilibria; Nash and Stackelberg solution concepts; multi-act games; Braess paradox; differential games; the relationship between the existence of solutions of Riccati equations and the existence of Nash equilibrium solutions; and infinite-horizon differential games.