Algorithms and Ordering Heuristics for Distributed Constraint Satisfaction Problems

A Constraint Satisfaction Problem (CSP) consists of a set of variables, a domain of values for each variable and a set of constraints. The objective is to assign a value for each variable such that all constraints are satisfied. CSPs continue to receive increased attention because of both their high complexity and their omnipresence in academic, industrial and even real-life problems. This is why they are the subject of intense research in both artificial intelligence and operations research. This book introduces the classic CSP and details several extensions/improvements of both formalisms and techniques in order to tackle a large variety of problems. Consistency, flexible, dynamic, distributed and learning aspects are discussed and illustrated using simple examples such as the n-queen problem. Contents 1. Foundations of CSP. 2. Consistency Reinforcement Techniques. 3. CSP Solving Algorithms. 4. Search Heuristics. 5. Learning Techniques. 6. Maximal Constraint Satisfaction Problems. 7. Constraint Satisfaction and Optimization Problems. 8. Distibuted Constraint Satisfaction Problems. About the Authors Khaled Ghedira is the general managing director of the Tunis Science City in Tunisia, Professor at the University of Tunis, as well as the founding president of the Tunisian Association of Artificial Intelligence and the founding director of the SOIE research laboratory. His research areas include MAS, CSP, transport and production logistics, metaheuristics and security in M/E-government. He has led several national and international research projects, supervised 30 PhD theses and more than 50 Master’s theses, co-authored about 300 journal, conference and book research papers, written two text books on metaheuristics and production logistics and co-authored three others.

This text is based on a simple and fully reactive computational model that allows for intuitive comprehension and logical designs. The principles and techniques presented can be applied to any distributed computing environment (e.g., distributed systems, communication networks, data networks, grid networks, internet, etc.). The text provides a wealth of unique material for learning how to design algorithms and protocols perform tasks efficiently in a distributed computing environment.

Nowadays, distributed systems are increasingly present, for public software applications as well as critical systems. software applications as well as critical systems. This title and Distributed Systems: Design and Algorithms – from the same editors – introduce the underlying concepts, the associated design techniques and the related security issues. The objective of this book is to describe the state of the art of the formal methods for the analysis of distributed systems. Numerous issues remain open and are the topics of major research projects. One current research trend consists of profoundly mixing the design, modeling, verification and implementation stages. This prototyping-based approach is centered around the concept of model refinement. This book is more specifically intended for readers that wish to gain an overview of the application of formal methods in the design of distributed systems. Master’s and PhD students, as well as engineers in industry, will find a global understanding of the techniques as well as references to the most up-to-date works in this area.

The essential guide to solving algorithmic and networking problems in commercial computer games, revised and extended Algorithms and Networking for Computer Games, Second Edition is written from the perspective of the computer scientist. Combining algorithmic knowledge and game-related problems, it explores the most common problems encountered in game programing. The first part of the book presents practical algorithms for solving “classical” topics, such as random numbers, procedural generation, tournaments, group formations and game trees. The authors also focus on how to find a path in, create the terrain of, and make decisions in the game world. The second part introduces networking related problems in computer games, focusing on four key questions: how to hide the inherent communication delay, how to best exploit limited network resources, how to cope with cheating and how to measure the on-line game data. Thoroughly revised, updated, and expanded to reflect the many constituent changes occurring in the commercial gaming industry since the original, this Second Edition, like the first, is a timely, comprehensive resource offering deeper algorithmic insight and more extensive coverage of game-specific networking problems than ordinarily encountered in game development books. Algorithms and Networking for Computer Games, Second Edition: Provides algorithmic solutions in pseudo-code format, which emphasises the idea behind the solution, and can easily be written into a programming language of choice Features a section on the Synthetic player, covering decision-making, influence maps, finite-state machines, flocking, fuzzy sets, and probabilistic reasoning and noise generation Contains in-depth treatment of network communication, including dead-reckoning, local perception filters, cheating prevention and on-line metrics Now includes 73 ready-to-use algorithms and 247 illustrative exercises Algorithms and Networking for Computer Games, Second Edition is a must-have resource for advanced undergraduate and graduate students taking computer game related courses, postgraduate researchers in game-related topics, and developers interested in deepening their knowledge of the theoretical underpinnings of computer games and in learning new approaches to game design and programming.

Algorithms and Networking for Computer Games is an essential guide to solving the algorithmic and networking problems of modern commercial computer games, written from the perspective of a computer scientist. Combining algorithmic knowledge and game-related problems, the authors discuss all the common difficulties encountered in game programming. The first part of the book tackles algorithmic problems by presenting how they can be solved practically. As well as «classical» topics such as random numbers, tournaments and game trees, the authors focus on how to find a path in, create the terrain of, and make decisions in the game world. Part two introduces networking related problems in computer games and focuses on three key questions: how to hide the inherent communication delay, how to utilize limited network resources, and how to cope with cheating. Algorithms and Networking for Computer Games provides a comprehensive resource that offers deeper algorithmic insight into game programming and explains game-specific network considerations. Read on for… Algorithmic solutions in pseudo code format, which not only emphasizes the idea behind the solution, but also can easily be written into the programming language of your choice. A section on the Synthetic player, covering decision-making, influence maps, finite-state machines, flocking, fuzzy sets and probabilistic reasoning. In-depth treatment of network communication including dead reckoning, local perception filters and cheating prevention. 51 ready-to-use algorithms and 178 illustrative exercises. Algorithms and Networking for Computer Games is a must-read text for advanced undergraduate and graduate students on computer game-related courses, postgraduate researchers in game-related topics, and game developers interested in new approaches and the theoretical background to games.

By providing expositions to modeling principles, theories, computational solutions, and open problems, this reference presents a full scope on relevant biological phenomena, modeling frameworks, technical challenges, and algorithms. Up-to-date developments of structures of biomolecules, systems biology, advanced models, and algorithms Sampling techniques for estimating evolutionary rates and generating molecular structures Accurate computation of probability landscape of stochastic networks, solving discrete chemical master equations End-of-chapter exercises

An invaluable reference for anyone designing new parallel or distributed systems. Includes detailed case studies of specific systems from Stanford, MIT, and other leading research universities. The authors emphasize performance, surveying all available techniques.

A cookbook of algorithms for common image processing applications Thanks to advances in computer hardware and software, algorithms have been developed that support sophisticated image processing without requiring an extensive background in mathematics. This bestselling book has been fully updated with the newest of these, including 2D vision methods in content-based searches and the use of graphics cards as image processing computational aids. It’s an ideal reference for software engineers and developers, advanced programmers, graphics programmers, scientists, and other specialists who require highly specialized image processing. Algorithms now exist for a wide variety of sophisticated image processing applications required by software engineers and developers, advanced programmers, graphics programmers, scientists, and related specialists This bestselling book has been completely updated to include the latest algorithms, including 2D vision methods in content-based searches, details on modern classifier methods, and graphics cards used as image processing computational aids Saves hours of mathematical calculating by using distributed processing and GPU programming, and gives non-mathematicians the shortcuts needed to program relatively sophisticated applications. Algorithms for Image Processing and Computer Vision, 2nd Edition provides the tools to speed development of image processing applications.

A one-stop resource for the use of algorithms and protocols in wireless sensor networks From an established international researcher in the field, this edited volume provides readers with comprehensive coverage of the fundamental algorithms and protocols for wireless sensor networks. It identifies the research that needs to be conducted on a number of levels to design and assess the deployment of wireless sensor networks, and provides an in-depth analysis of the development of the next generation of heterogeneous wireless sensor networks. Divided into nineteen succinct chapters, the book covers: mobility management and resource allocation algorithms; communication models; energy and power consumption algorithms; performance modeling and simulation; authentication and reputation mechanisms; algorithms for wireless sensor and mesh networks; and algorithm methods for pervasive and ubiquitous computing; among other topics. Complete with a set of challenging exercises, this book is a valuable resource for electrical engineers, computer engineers, network engineers, and computer science specialists. Useful for instructors and students alike, Algorithms and Protocols for Wireless Sensor Networks is an ideal textbook for advanced undergraduate and graduate courses in computer science, electrical engineering,and network engineering.

A detailed review of a wide range of meta-heuristic and evolutionary algorithms in a systematic manner and how they relate to engineering optimization problems This book introduces the main metaheuristic algorithms and their applications in optimization. It describes 20 leading meta-heuristic and evolutionary algorithms and presents discussions and assessments of their performance in solving optimization problems from several fields of engineering. The book features clear and concise principles and presents detailed descriptions of leading methods such as the pattern search (PS) algorithm, the genetic algorithm (GA), the simulated annealing (SA) algorithm, the Tabu search (TS) algorithm, the ant colony optimization (ACO), and the particle swarm optimization (PSO) technique. Chapter 1 of Meta-heuristic and Evolutionary Algorithms for Engineering Optimization provides an overview of optimization and defines it by presenting examples of optimization problems in different engineering domains. Chapter 2 presents an introduction to meta-heuristic and evolutionary algorithms and links them to engineering problems. Chapters 3 to 22 are each devoted to a separate algorithm— and they each start with a brief literature review of the development of the algorithm, and its applications to engineering problems. The principles, steps, and execution of the algorithms are described in detail, and a pseudo code of the algorithm is presented, which serves as a guideline for coding the algorithm to solve specific applications. This book: Introduces state-of-the-art metaheuristic algorithms and their applications to engineering optimization; Fills a gap in the current literature by compiling and explaining the various meta-heuristic and evolutionary algorithms in a clear and systematic manner; Provides a step-by-step presentation of each algorithm and guidelines for practical implementation and coding of algorithms; Discusses and assesses the performance of metaheuristic algorithms in multiple problems from many fields of engineering; Relates optimization algorithms to engineering problems employing a unifying approach. Meta-heuristic and Evolutionary Algorithms for Engineering Optimization is a reference intended for students, engineers, researchers, and instructors in the fields of industrial engineering, operations research, optimization/mathematics, engineering optimization, and computer science. OMID BOZORG-HADDAD, PhD, is Professor in the Department of Irrigation and Reclamation Engineering at the University of Tehran, Iran. MOHAMMAD SOLGI, M.Sc., is Teacher Assistant for M.Sc. courses at the University of Tehran, Iran. HUGO A. LO?ICIGA, PhD, is Professor in the Department of Geography at the University of California, Santa Barbara, United States of America.