Optimization Of Stochastic Discrete Systems And Control On Complex Networks
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Optimization Of Stochastic Discrete Systems And Control On Complex Networks
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Author : Dmitrii Lozovanu
language : en
Publisher: Springer
Release Date : 2014-11-27
Optimization Of Stochastic Discrete Systems And Control On Complex Networks written by Dmitrii Lozovanu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-27 with Business & Economics categories.
This book presents the latest findings on stochastic dynamic programming models and on solving optimal control problems in networks. It includes the authors’ new findings on determining the optimal solution of discrete optimal control problems in networks and on solving game variants of Markov decision problems in the context of computational networks. First, the book studies the finite state space of Markov processes and reviews the existing methods and algorithms for determining the main characteristics in Markov chains, before proposing new approaches based on dynamic programming and combinatorial methods. Chapter two is dedicated to infinite horizon stochastic discrete optimal control models and Markov decision problems with average and expected total discounted optimization criteria, while Chapter three develops a special game-theoretical approach to Markov decision processes and stochastic discrete optimal control problems. In closing, the book’s final chapter is devoted to finite horizon stochastic control problems and Markov decision processes. The algorithms developed represent a valuable contribution to the important field of computational network theory.
Control Techniques For Complex Networks
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Author : Sean Meyn
language : en
Publisher: Cambridge University Press
Release Date : 2008
Control Techniques For Complex Networks written by Sean Meyn 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 2008 with Computers categories.
From foundations to state-of-the-art; the tools and philosophy you need to build network models.
Algorithmic Decision Theory
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Author : Jörg Rothe
language : en
Publisher: Springer
Release Date : 2017-10-13
Algorithmic Decision Theory written by Jörg Rothe and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-13 with Computers categories.
This book constitutes the conference proceedings of the 5th International Conference on Algorithmic Decision Theory , ADT 2017, held in Luxembourg, in October 2017.The 22 full papers presented together with 6 short papers, 4 keynote abstracts, and 6 Doctoral Consortium papers, were carefully selected from 45 submissions. The papers are organized in topical sections on preferences and multi-criteria decision aiding; decision making and voting; game theory and decision theory; and allocation and matching.
Performance Analysis Of Complex Networks And Systems
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Author : Piet Van Mieghem
language : en
Publisher: Cambridge University Press
Release Date : 2014-04-24
Performance Analysis Of Complex Networks And Systems written by Piet Van Mieghem 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 2014-04-24 with Computers categories.
Provides the mathematical, stochastic and graph theoretic methods to analyse the performance and robustness of complex networks and systems.
Cooperative Control Of Complex Network Systems With Dynamic Topologies
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Author : Guanghui Wen
language : en
Publisher: CRC Press
Release Date : 2021-07-01
Cooperative Control Of Complex Network Systems With Dynamic Topologies written by Guanghui Wen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-01 with Technology & Engineering categories.
Far from being separate entities, many social and engineering systems can be considered as complex network systems (CNSs) associated with closely linked interactions with neighbouring entities such as the Internet and power grids. Roughly speaking, a CNS refers to a networking system consisting of lots of interactional individuals, exhibiting fascinating collective behaviour that cannot always be anticipated from the inherent properties of the individuals themselves. As one of the most fundamental examples of cooperative behaviour, consensus within CNSs (or the synchronization of complex networks) has gained considerable attention from various fields of research, including systems science, control theory and electrical engineering. This book mainly studies consensus of CNSs with dynamics topologies - unlike most existing books that have focused on consensus control and analysis for CNSs under a fixed topology. As most practical networks have limited communication ability, switching graphs can be used to characterize real-world communication topologies, leading to a wider range of practical applications. This book provides some novel multiple Lyapunov functions (MLFs), good candidates for analysing the consensus of CNSs with directed switching topologies, while each chapter provides detailed theoretical analyses according to the stability theory of switched systems. Moreover, numerical simulations are provided to validate the theoretical results. Both professional researchers and laypeople will benefit from this book.
Synchronization Control Of Markovian Complex Neural Networks With Time Varying Delays
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Author : Junyi Wang
language : en
Publisher: Springer Nature
Release Date : 2023-11-28
Synchronization Control Of Markovian Complex Neural Networks With Time Varying Delays written by Junyi 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 2023-11-28 with Technology & Engineering categories.
This monograph studies the synchronization control of Markovian complex neural networks with time-varying delays, and the structure of the book is summarized as follows. Chapter 1 introduces the system description and some background knowledges, and also addresses the motivations of this monograph. In Chapter 2, the stochastic synchronization issue of Markovian coupled neural networks with partially unknown transition rates and random coupling strengths is investigated. In Chapter 3, the local synchronization issue of Markovian neutral complex networks with partially information of transition rates is investigated. The new delay-dependent synchronization criteria in terms of LMIs are derived, which depends on the upper and lower bounds of the delays. In Chapter 4, the local synchronization issue of Markovian nonlinear coupled neural networks with uncertain and partially unknown transition rates is investigated. The less conservative local synchronization criteria containing the bounds of delay and delay derivative are obtained based on the novel augmented Lyapunov-Krasovskii functional and a new integral inequality. In Chapter 5, the sampled-data synchronization issue of delayed complex networks with aperiodic sampling interval is investigated based on enhanced input delay approach, which makes full use of the upper bound of the variable sampling interval and the sawtooth structure information of varying input delay. In Chapter 6, the sampled-data synchronization issue of Markovian coupled neural networks with mode-dependent interval time-varying delays and aperiodic sampling intervals is investigated based on an enhanced input delay approach. Furthermore, the mode-dependent sampled-data controllers are proposed based on the delay dependent synchronization criteria. In Chapter 7, the synchronization issue of inertial neural networks with time-varying delays and generally Markovian jumping is investigated. In Chapter 8, we conclude the monograph by briefly summarizing the main theoretical findings.
Complex Networks Ix
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Author : Sean Cornelius
language : en
Publisher: Springer
Release Date : 2018-02-15
Complex Networks Ix written by Sean Cornelius and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-15 with Science categories.
This book aims to bring together researchers and practitioners working across domains and research disciplines to measure, model, and visualize complex networks. It collects the works presented at the 9th International Conference on Complex Networks (CompleNet) in Boston, MA, March, 2018. With roots in physical, information and social science, the study of complex networks provides a formal set of mathematical methods, computational tools and theories to describe, prescribe and predict dynamics and behaviors of complex systems. Despite their diversity, whether the systems are made up of physical, technological, informational, or social networks, they share many common organizing principles and thus can be studied with similar approaches. This book provides a view of the state-of-the-art in this dynamic field and covers topics such as group decision-making, brain and cellular connectivity, network controllability and resiliency, online activism, recommendation systems, and cyber security.
Discrete Networked Dynamic Systems
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Author : Magdi S. Mahmoud
language : en
Publisher: Academic Press
Release Date : 2020-10-22
Discrete Networked Dynamic Systems written by Magdi S. Mahmoud and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-22 with Technology & Engineering categories.
Discrete Networked Dynamic Systems: Analysis and Performance provides a high-level treatment of a general class of linear discrete-time dynamic systems interconnected over an information network, exchanging relative state measurements or output measurements. It presents a systematic analysis of the material and provides an account to the math development in a unified way. The topics in this book are structured along four dimensions: Agent, Environment, Interaction, and Organization, while keeping global (system-centered) and local (agent-centered) viewpoints. The focus is on the wide-sense consensus problem in discrete networked dynamic systems. The authors rely heavily on algebraic graph theory and topology to derive their results. It is known that graphs play an important role in the analysis of interactions between multiagent/distributed systems. Graph-theoretic analysis provides insight into how topological interactions play a role in achieving coordination among agents. Numerous types of graphs exist in the literature, depending on the edge set of G. A simple graph has no self-loop or edges. Complete graphs are simple graphs with an edge connecting any pair of vertices. The vertex set in a bipartite graph can be partitioned into disjoint non-empty vertex sets, whereby there is an edge connecting every vertex in one set to every vertex in the other set. Random graphs have fixed vertex sets, but the edge set exhibits stochastic behavior modeled by probability functions. Much of the studies in coordination control are based on deterministic/fixed graphs, switching graphs, and random graphs. - This book addresses advanced analytical tools for characterization control, estimation and design of networked dynamic systems over fixed, probabilistic and time-varying graphs - Provides coherent results on adopting a set-theoretic framework for critically examining problems of the analysis, performance and design of discrete distributed systems over graphs - Deals with both homogeneous and heterogeneous systems to guarantee the generality of design results
Recent Awards In Engineering
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Author :
language : en
Publisher:
Release Date : 1983
Recent Awards In Engineering written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Engineering categories.
Reinforcement Learning And Stochastic Optimization
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Author : Warren B. Powell
language : en
Publisher: John Wiley & Sons
Release Date : 2022-03-15
Reinforcement Learning And Stochastic Optimization written by Warren B. Powell and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-15 with Mathematics categories.
REINFORCEMENT LEARNING AND STOCHASTIC OPTIMIZATION Clearing the jungle of stochastic optimization Sequential decision problems, which consist of “decision, information, decision, information,” are ubiquitous, spanning virtually every human activity ranging from business applications, health (personal and public health, and medical decision making), energy, the sciences, all fields of engineering, finance, and e-commerce. The diversity of applications attracted the attention of at least 15 distinct fields of research, using eight distinct notational systems which produced a vast array of analytical tools. A byproduct is that powerful tools developed in one community may be unknown to other communities. Reinforcement Learning and Stochastic Optimization offers a single canonical framework that can model any sequential decision problem using five core components: state variables, decision variables, exogenous information variables, transition function, and objective function. This book highlights twelve types of uncertainty that might enter any model and pulls together the diverse set of methods for making decisions, known as policies, into four fundamental classes that span every method suggested in the academic literature or used in practice. Reinforcement Learning and Stochastic Optimization is the first book to provide a balanced treatment of the different methods for modeling and solving sequential decision problems, following the style used by most books on machine learning, optimization, and simulation. The presentation is designed for readers with a course in probability and statistics, and an interest in modeling and applications. Linear programming is occasionally used for specific problem classes. The book is designed for readers who are new to the field, as well as those with some background in optimization under uncertainty. Throughout this book, readers will find references to over 100 different applications, spanning pure learning problems, dynamic resource allocation problems, general state-dependent problems, and hybrid learning/resource allocation problems such as those that arose in the COVID pandemic. There are 370 exercises, organized into seven groups, ranging from review questions, modeling, computation, problem solving, theory, programming exercises and a "diary problem" that a reader chooses at the beginning of the book, and which is used as a basis for questions throughout the rest of the book.