Distributed Optimization Game And Learning Algorithms
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Distributed Optimization Game And Learning Algorithms
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Author : Huiwei Wang
language : en
Publisher: Springer Nature
Release Date : 2021-01-04
Distributed Optimization Game And Learning Algorithms written by Huiwei Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-04 with Technology & Engineering categories.
This book provides the fundamental theory of distributed optimization, game and learning. It includes those working directly in optimization,-and also many other issues like time-varying topology, communication delay, equality or inequality constraints,-and random projections. This book is meant for the researcher and engineer who uses distributed optimization, game and learning theory in fields like dynamic economic dispatch, demand response management and PHEV routing of smart grids.
Game Theoretic Learning And Distributed Optimization In Memoryless Multi Agent Systems
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Author : Tatiana Tatarenko
language : en
Publisher: Springer
Release Date : 2017-09-19
Game Theoretic Learning And Distributed Optimization In Memoryless Multi Agent Systems written by Tatiana Tatarenko and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-19 with Science categories.
This book presents new efficient methods for optimization in realistic large-scale, multi-agent systems. These methods do not require the agents to have the full information about the system, but instead allow them to make their local decisions based only on the local information, possibly obtained during communication with their local neighbors. The book, primarily aimed at researchers in optimization and control, considers three different information settings in multi-agent systems: oracle-based, communication-based, and payoff-based. For each of these information types, an efficient optimization algorithm is developed, which leads the system to an optimal state. The optimization problems are set without such restrictive assumptions as convexity of the objective functions, complicated communication topologies, closed-form expressions for costs and utilities, and finiteness of the system’s state space.
Distributed Optimization And Learning
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Author : Zhongguo Li
language : en
Publisher: Elsevier
Release Date : 2024-07-18
Distributed Optimization And Learning written by Zhongguo Li and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-18 with Technology & Engineering categories.
Distributed Optimization and Learning: A Control-Theoretic Perspective illustrates the underlying principles of distributed optimization and learning. The book presents a systematic and self-contained description of distributed optimization and learning algorithms from a control-theoretic perspective. It focuses on exploring control-theoretic approaches and how those approaches can be utilized to solve distributed optimization and learning problems over network-connected, multi-agent systems. As there are strong links between optimization and learning, this book provides a unified platform for understanding distributed optimization and learning algorithms for different purposes. - Provides a series of the latest results, including but not limited to, distributed cooperative and competitive optimization, machine learning, and optimal resource allocation - Presents the most recent advances in theory and applications of distributed optimization and machine learning, including insightful connections to traditional control techniques - Offers numerical and simulation results in each chapter in order to reflect engineering practice and demonstrate the main focus of developed analysis and synthesis approaches
Distributed Optimization Based Control Of Multi Agent Networks In Complex Environments
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Author : Minghui Zhu
language : en
Publisher: Springer
Release Date : 2015-06-11
Distributed Optimization Based Control Of Multi Agent Networks In Complex Environments written by Minghui Zhu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-11 with Technology & Engineering categories.
This book offers a concise and in-depth exposition of specific algorithmic solutions for distributed optimization based control of multi-agent networks and their performance analysis. It synthesizes and analyzes distributed strategies for three collaborative tasks: distributed cooperative optimization, mobile sensor deployment and multi-vehicle formation control. The book integrates miscellaneous ideas and tools from dynamic systems, control theory, graph theory, optimization, game theory and Markov chains to address the particular challenges introduced by such complexities in the environment as topological dynamics, environmental uncertainties, and potential cyber-attack by human adversaries. The book is written for first- or second-year graduate students in a variety of engineering disciplines, including control, robotics, decision-making, optimization and algorithms and with backgrounds in aerospace engineering, computer science, electrical engineering, mechanical engineering and operations research. Researchers in these areas may also find the book useful as a reference.
Networked Control Systems
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Author : Alberto Bemporad
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-10-14
Networked Control Systems written by Alberto Bemporad and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-14 with Mathematics categories.
This book nds its origin in the WIDE PhD School on Networked Control Systems, which we organized in July 2009 in Siena, Italy. Having gathered experts on all the aspects of networked control systems, it was a small step to go from the summer school to the book, certainly given the enthusiasm of the lecturers at the school. We felt that a book collecting overviewson the important developmentsand open pr- lems in the eld of networked control systems could stimulate and support future research in this appealing area. Given the tremendouscurrentinterests in distributed control exploiting wired and wireless communication networks, the time seemed to be right for the book that lies now in front of you. The goal of the book is to set out the core techniques and tools that are ava- able for the modeling, analysis and design of networked control systems. Roughly speaking, the book consists of three parts. The rst part presents architectures for distributed control systems and models of wired and wireless communication n- works. In particular, in the rst chapter important technological and architectural aspects on distributed control systems are discussed. The second chapter provides insight in the behavior of communication channels in terms of delays, packet loss and information constraints leading to suitable modeling paradigms for commu- cation networks.
Proceedings Of 2023 Chinese Intelligent Systems Conference
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Author : Yingmin Jia
language : en
Publisher: Springer Nature
Release Date : 2023-10-07
Proceedings Of 2023 Chinese Intelligent Systems Conference written by Yingmin Jia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-07 with Technology & Engineering categories.
This book constitutes the proceedings of the 19th Chinese Intelligent Systems Conference, CISC 2023, which was held during October 14–15, 2023, in Ningbo, Zhejiang, China. The book focuses on new theoretical results and techniques in the field of intelligent systems and control. This is achieved by providing in-depth studies of a number of important topics such as multi-agent systems, complex networks, intelligent robots, complex systems theory and swarm behavior, event-driven and data-driven control, robust and adaptive control, big data and brain science, process control, intelligent sensors and detection technology, deep learning and learning control, navigation and control of aerial vehicles, and so on. The book is particularly suitable for readers interested in learning intelligent systems and control and artificial intelligence. The book can benefit researchers, engineers and graduate students.
Distributed Strategic Learning For Wireless Engineers
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Author : Hamidou Tembine
language : en
Publisher: CRC Press
Release Date : 2018-10-08
Distributed Strategic Learning For Wireless Engineers written by Hamidou Tembine and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-08 with Mathematics categories.
Although valued for its ability to allow teams to collaborate and foster coalitional behaviors among the participants, game theory’s application to networking systems is not without challenges. Distributed Strategic Learning for Wireless Engineers illuminates the promise of learning in dynamic games as a tool for analyzing network evolution and underlines the potential pitfalls and difficulties likely to be encountered. Establishing the link between several theories, this book demonstrates what is needed to learn strategic interaction in wireless networks under uncertainty, randomness, and time delays. It addresses questions such as: How much information is enough for effective distributed decision making? Is having more information always useful in terms of system performance? What are the individual learning performance bounds under outdated and imperfect measurement? What are the possible dynamics and outcomes if the players adopt different learning patterns? If convergence occurs, what is the convergence time of heterogeneous learning? What are the issues of hybrid learning? How can one develop fast and efficient learning schemes in scenarios where some players have more information than the others? What is the impact of risk-sensitivity in strategic learning systems? How can one construct learning schemes in a dynamic environment in which one of the players do not observe a numerical value of its own-payoffs but only a signal of it? How can one learn "unstable" equilibria and global optima in a fully distributed manner? The book provides an explicit description of how players attempt to learn over time about the game and about the behavior of others. It focuses on finite and infinite systems, where the interplay among the individual adjustments undertaken by the different players generates different learning dynamics, heterogeneous learning, risk-sensitive learning, and hybrid dynamics.
Scaling Up Machine Learning
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Author : Ron Bekkerman
language : en
Publisher: Cambridge University Press
Release Date : 2012
Scaling Up Machine Learning written by Ron Bekkerman and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computers categories.
This integrated collection covers a range of parallelization platforms, concurrent programming frameworks and machine learning settings, with case studies.
Cooperative And Graph Signal Processing
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Author : Petar Djuric
language : en
Publisher: Academic Press
Release Date : 2018-07-04
Cooperative And Graph Signal Processing written by Petar Djuric and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-04 with Computers categories.
Cooperative and Graph Signal Processing: Principles and Applications presents the fundamentals of signal processing over networks and the latest advances in graph signal processing. A range of key concepts are clearly explained, including learning, adaptation, optimization, control, inference and machine learning. Building on the principles of these areas, the book then shows how they are relevant to understanding distributed communication, networking and sensing and social networks. Finally, the book shows how the principles are applied to a range of applications, such as Big data, Media and video, Smart grids, Internet of Things, Wireless health and Neuroscience. With this book readers will learn the basics of adaptation and learning in networks, the essentials of detection, estimation and filtering, Bayesian inference in networks, optimization and control, machine learning, signal processing on graphs, signal processing for distributed communication, social networks from the perspective of flow of information, and how to apply signal processing methods in distributed settings. - Presents the first book on cooperative signal processing and graph signal processing - Provides a range of applications and application areas that are thoroughly covered - Includes an editor in chief and associate editor from the IEEE Transactions on Signal Processing and Information Processing over Networks who have recruited top contributors for the book
Spontaneous Order
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Author : H. Peyton Young
language : en
Publisher: Oxford University Press
Release Date : 2024-10-10
Spontaneous Order written by H. Peyton Young and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-10 with Business & Economics categories.
Spontaneous Order brings together Peyton Young's research on evolutionary game theory and its diverse applications across a wide range of academic disciplines, including economics, sociology, philosophy, biology, computer science, and engineering. Enhanced with an introductory essay and commentaries, the book pulls together the author's work thematically to provide a valuable resource for scholars of economic theory. Young argues that equilibrium behaviors often coalesce from the interactions and experiences of many dispersed individuals acting with fragmentary knowledge of the world, rather than (as is often assumed in economics) from the actions of fully rational agents with commonly held beliefs. The author presents a unified and rigorous account of how such 'bottom-up' evolutionary processes work, using recent advances in stochastic dynamical systems theory. This analytical framework illuminates how social norms and institutions evolve, how social and technical innovations spread in society, and how these processes depend on adaptive learning behavior by human subjects.