Author : Adrian Petcu
Publisher : IOS Press
Page : 304 pages
File Size : 36,81 MB
Release : 2009
Category : Computers
ISBN : 158603989X
Addresses three major issues that arise in Distributed Constraint Optimization Problems (DCOP): efficient optimization algorithms, dynamic and open environments, and manipulations from self-interested users. This book introduces a series of DCOP algorithms, which are based on dynamic programming.
Author : Amnon Meisels
Publisher : Springer Science & Business Media
Page : 223 pages
File Size : 39,35 MB
Release : 2008
Category : Computers
ISBN : 1848000391
The well defined model of distributed constraints satisfaction and optimization (DisCSPs/DisCOPs) can serve as the basis for the design and investigation of distributed search algorithms, of protocols and of negotiations and search. This book presents a comprehensive discussion on the field of distributed constraints, its algorithms and its active research areas. The book introduces distributed constraint satisfaction and optimization problems and describes the underlying model.
Author : Simon Michalowsky
Publisher : Logos Verlag Berlin GmbH
Page : 165 pages
File Size : 49,46 MB
Release : 2020-04-17
Category : Technology & Engineering
ISBN : 3832550909
Optimization algorithms are the backbone of many modern technologies. In this thesis, we address the analysis and design of optimization algorithms from a systems theoretic viewpoint. By properly recasting the algorithm design as a controller synthesis problem, we derive methods that enable a systematic design of tailored optimization algorithms. We consider two specific classes of optimization algorithms: (i) distributed, and (ii) robust optimization algorithms. Concerning (i), we utilize ideas from geometric control in an innovative fashion to derive a novel methodology that enables the design of distributed optimization algorithms under minimal assumptions on the graph topology and the structure of the optimization problem. Concerning (ii), we employ robust control techniques to establish a framework for the analysis of existing algorithms as well as the design of novel robust optimization algorithms with specified guarantees.
Author : John P. Davin
Publisher :
Page : 49 pages
File Size : 43,32 MB
Release : 2005
Category : Constraint optimization
ISBN :
Abstract: "A class of problems known as Distributed Constraint Optimization Problems (DCOP) has become a growing research interest in computer science because of its difficulty (NP-Complete) and many real-world applications (meeting scheduling, sensor networks, military planning). In this thesis we identify two types of centralization relevant to DCOPs: algorithmic centralization, in which a DCOP algorithm actively centralizes part (or all) of the problem structure, and domain centralization, in which inherent centralization already exists in the domain specification. We explore algorithmic centralization by empirically studying Adopt and OptAPO, two DCOP algorithms which differ in the amount of centralization they use. Our results show that centralizing a problem's structure decreases communication overhead, but increases local computation. We compare the algorithms through our contribution of a new performance metric, Cycle-Based Runtime, which takes both communication costs and local computation time into account. We then explore domain centralization by studying meeting scheduling, which has problem structure clustered at scheduling agents. We present a novel variant of Adopt, called AdoptMVA, which uses a centralized search within agents to take advantage of the partially centralized structure. We show that when agent ordering is controlled for, AdoptMVA outperforms Adopt in situations where communication costs are high. We contribute a Branch & Bound search heuristic which works well for meeting scheduling problems with multiple variables per agent. We also empirically experiment with meeting scheduling, showing that meeting size is in some cases a better indicator of solution difficulty than the number of agents in a problem."
Author : Huaqing Li
Publisher : Springer Nature
Page : 243 pages
File Size : 11,94 MB
Release : 2020-08-04
Category : Technology & Engineering
ISBN : 9811561095
This book offers a valuable reference guide for researchers in distributed optimization and for senior undergraduate and graduate students alike. Focusing on the natures and functions of agents, communication networks and algorithms in the context of distributed optimization for networked control systems, this book introduces readers to the background of distributed optimization; recent developments in distributed algorithms for various types of underlying communication networks; the implementation of computation-efficient and communication-efficient strategies in the execution of distributed algorithms; and the frameworks of convergence analysis and performance evaluation. On this basis, the book then thoroughly studies 1) distributed constrained optimization and the random sleep scheme, from an agent perspective; 2) asynchronous broadcast-based algorithms, event-triggered communication, quantized communication, unbalanced directed networks, and time-varying networks, from a communication network perspective; and 3) accelerated algorithms and stochastic gradient algorithms, from an algorithm perspective. Finally, the applications of distributed optimization in large-scale statistical learning, wireless sensor networks, and for optimal energy management in smart grids are discussed.
Author : Ariel Rosenfeld
Publisher : Springer Nature
Page : 292 pages
File Size : 11,49 MB
Release : 2021-07-20
Category : Computers
ISBN : 3030822540
This book constitutes the revised post-conference proceedings of the 18th European Conference on Multi-Agent Systems, EUMAS 2021. The conference was held online in June, 2021. 16 full papers are presented in this volume, each of which carefully reviewed and selected from a total of 51 submissions. The papers report on both early and mature research and cover a wide range of topics in the field of multi-agent systems.
Author : Gerhard Weiss
Publisher : MIT Press
Page : 917 pages
File Size : 30,68 MB
Release : 2013-03-08
Category : Computers
ISBN : 0262018896
This is the first comprehensive introduction to multiagent systems and contemporary distributed artificial intelligence that is suitable as a textbook.
Author : Rosa G. González-Ramírez
Publisher : Springer
Page : 190 pages
File Size : 42,14 MB
Release : 2014-09-24
Category : Computers
ISBN : 3319114212
This book constitutes the refereed proceedings of the 5th International Conference on Computational Logistics, ICCL 2014, held in Valparaiso, Chile, in September 2014. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in the book. They are organized in topical sections entitled: optimization of transport problems; container terminal applications; simulation and environmental sustainability applications.
Author : Md. Mosaddek Khan
Publisher :
Page : 119 pages
File Size : 19,43 MB
Release : 2018
Category :
ISBN :
Author : Mohamed Wahbi
Publisher : John Wiley & Sons
Page : 188 pages
File Size : 21,48 MB
Release : 2013-07-01
Category : Computers
ISBN : 1118753429
DisCSP (Distributed Constraint Satisfaction Problem) is a general framework for solving distributed problems arising in Distributed Artificial Intelligence. A wide variety of problems in artificial intelligence are solved using the constraint satisfaction problem paradigm. However, there are several applications in multi-agent coordination that are of a distributed nature. In this type of application, the knowledge about the problem, that is, variables and constraints, may be logically or geographically distributed among physical distributed agents. This distribution is mainly due to privacy and/or security requirements. Therefore, a distributed model allowing a decentralized solving process is more adequate to model and solve such kinds of problem. The distributed constraint satisfaction problem has such properties. Contents Introduction Part 1. Background on Centralized and Distributed Constraint Reasoning 1. Constraint Satisfaction Problems 2. Distributed Constraint Satisfaction Problems Part 2. Synchronous Search Algorithms for DisCSPs 3. Nogood Based Asynchronous Forward Checking (AFC-ng) 4. Asynchronous Forward Checking Tree (AFC-tree) 5. Maintaining Arc Consistency Asynchronously in Synchronous Distributed Search Part 3. Asynchronous Search Algorithms and Ordering Heuristics for DisCSPs 6. Corrigendum to “Min-domain Retroactive Ordering for Asynchronous Backtracking” 7. Agile Asynchronous BackTracking (Agile-ABT) Part 4. DisChoco 2.0: A Platform for Distributed Constraint Reasoning 8. DisChoco 2.0 9. Conclusion About the Authors Mohamed Wahbi is currently an associate lecturer at Ecole des Mines de Nantes in France. He received his PhD degree in Computer Science from University Montpellier 2, France and Mohammed V University-Agdal, Morocco in 2012 and his research focused on Distributed Constraint Reasoning.
