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This dissertation by Shervin Parvini Ahmadi explores distributed optimization techniques for control and estimation in large-scale systems. The work addresses the challenges posed by centralized optimization, such as computational limitations and privacy concerns, and proposes distributed approaches that leverage parallelism and message passing. Key contributions include a distributed primal-dual algorithm for linear model predictive control, a tailored algorithm for nonlinear least squares in sensor networks, and an extended message passing framework for non-convex problems. The research demonstrates the efficiency and scalability of these methods, highlighting their potential applications in control systems and localization problems. The intended audience includes researchers and practitioners in electrical engineering and optimization.

Distributed algorithms. --- Optimisation . . .

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This book explores the field of distributed optimization and learning, focusing on multi-agent systems and their applications in various domains such as robotics, autonomous vehicles, and smart grids. It delves into fundamental concepts like consensus control, cooperative and competitive optimization, and game theory. The authors aim to provide a comprehensive understanding of distributed algorithms and their convergence, as well as their practical applications in networked systems. The book is intended for researchers and practitioners in control systems, electrical engineering, and related fields, offering insights into both theoretical foundations and real-world implementations.

Multiagent systems. --- Distributed algorithms.

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Computer science. --- Compilers --- Distributed algorithms --- External interfaces for robotics

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Computer programming --- Distributed algorithms. --- Multiprocessors --- Parallel processing (Electronic computers) --- Parallel programming (Computer science)

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Distributed computing is at the heart of many applications. It arises as soon as one has to solve a problem in terms of entities -- such as processes, peers, processors, nodes, or agents -- that individually have only a partial knowledge of the many input parameters associated with the problem. In particular each entity cooperating towards the common goal cannot have an instantaneous knowledge of the current state of the other entities. Whereas parallel computing is mainly concerned with 'efficiency', and real-time computing is mainly concerned with 'on-time computing', distributed computing is mainly concerned with 'mastering uncertainty' created by issues such as the multiplicity of control flows, asynchronous communication, unstable behaviors, mobility, and dynamicity.   While some distributed algorithms consist of a few lines only, their behavior can be difficult to understand and their properties hard to state and prove. The aim of this book is to present in a comprehensive way the basic notions, concepts, and algorithms of distributed computing when the distributed entities cooperate by sending and receiving messages on top of an asynchronous network. The book is composed of seventeen chapters structured into six parts: distributed graph algorithms, in particular what makes them different from sequential or parallel algorithms; logical time and global states, the core of the book; mutual exclusion and resource allocation; high-level communication abstractions; distributed detection of properties; and distributed shared memory. The author establishes clear objectives per chapter and the content is supported throughout with illustrative examples, summaries, exercises, and annotated bibliographies.   This book constitutes an introduction to distributed computing and is suitable for advanced undergraduate students or graduate students in computer science and computer engineering, graduate students in mathematics interested in distributed computing, and practitioners and engineers involved in the design and implementation of distributed applications. The reader should have a basic knowledge of algorithms and operating systems.

Distributed algorithms --- Electronic data processing --- Distributed processing --- Mathematics --- Computer science. --- Computer hardware. --- Computer communication systems. --- Computer programming. --- Computers. --- Computer Science. --- Theory of Computation. --- Computer Communication Networks. --- Programming Techniques. --- Computer Hardware. --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace --- Computers --- Electronic computer programming --- Electronic digital computers --- Programming (Electronic computers) --- Coding theory --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Informatics --- Science --- Programming --- Information theory. --- Communication theory --- Communication --- Distributed algorithms. --- Mathematics. --- Electronic data processing - Distributed processing - Mathematics