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"To summarize, this book distills well over three decades worth of development in CSP and constraint processing in a single textbook. I wholeheartedly recommend it to students, researchers and practitioners in artificial intelligence, constraint programming and operations research who want to know more about the theory of constraint processing." - Roland H.C. Yap, National University of Singapore, in Theory and Practice of Logic Programming "This book provides a comprehensive and much needed introduction to the field by one of its foremost experts. It is beautifully written and presents a unifying framework capturing a wide range of techniques for processing symbolic, numerical, and probabilistic information." - Bart Selman, Cornell University "I've been waiting a long time for a good theoretical introduction to constraint programming. Rina Dechter's book is just this. If you want to understand why this technology works, and how to make it work for you, then I recommend you read this book." - Toby Walsh, Cork Constraint Computation Centre "The book is rigorous but it is not difficult to read. An abundance of examples illustrate concepts and algorithms. The reader is well guided through technical issues, so intuition is never hidden by technicalities." - Pedro Meseguer, Institut d'Investigacio en Intellingencia Artificial - Consejo Superior de Investigaciones Cientificas (IIIA-CSIC) "An indispensable resource for researchers and practitioners in AI and optimization." - Henry Kautz, University of Washington "a welcome introduction to the field of constraint satisfaction that will help researchers, educators, and students understand what constraint processing is about. It is a comprehensive book that can be used as a companion for courses on constraint satisfaction especially because the reader does not need to be an expert in the area to understand the text. The introductory character of the book makes it easy to read; nevertheless advanced students and researchers may also find deeper information on some topics there. Rina Dechter is an excellent researcher with contributions in many areas of constraint satisfaction . I strongly recommend reading this book to everyone who wants to know what is behind constraint satisfaction technology and I think that this book should definitely be in the bookshelf of everyone who teaches constraint satisfaction." - Roman Bartak, Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic
Kurzbeschreibung
Constraint satisfaction is a simple but powerful tool. Constraints identify the impossible and reduce the realm of possibilities to effectively focus on the possible, allowing for a natural declarative formulation of what must be satisfied, without expressing how. The field of constraint reasoning has matured over the last three decades with contributions from a diverse community of researchers in artificial intelligence, databases and programming languages, operations research, management science, and applied mathematics. Today, constraint problems are used to model cognitive tasks in vision, language comprehension, default reasoning, diagnosis, scheduling, temporal and spatial reasoning.
In Constraint Processing, Rina Dechter, synthesizes these contributions, along with her own significant work, to provide the first comprehensive examination of the theory that underlies constraint processing algorithms. Throughout, she focuses on fundamental tools and principles, emphasizing the representation and analysis of algorithms.
In diesem Buch
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Einleitungssatz
We regularly encounter constraint in our day-to-day lives-for instance, a finite amount of memory in our PCs, seats in the car, hours in the day, money in the bank. Lesen Sie die erste Seite
Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Stichwortverzeichnis
We regularly encounter constraint in our day-to-day lives-for instance, a finite amount of memory in our PCs, seats in the car, hours in the day, money in the bank. Lesen Sie die erste Seite
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9 Rezensionen
7 von 8 Kunden fanden die folgende Rezension hilfreich
Chapeau bas!
2. April 2004
Format:Gebundene Ausgabe
This book covers both introductory and advanced material. It is a
solid resource for introducing students to the basic mechanisms of
Constraint Processing and for training the future generation of
researchers in the field. It is also an invaluable tool for
perfecting the knowledge of the seasoned researcher in topics beyond
his/her particular expertise.
solid resource for introducing students to the basic mechanisms of
Constraint Processing and for training the future generation of
researchers in the field. It is also an invaluable tool for
perfecting the knowledge of the seasoned researcher in topics beyond
his/her particular expertise.
Its coverage of the relationship between relational algebra and
Constraint Satisfaction is unique and bound to inspire new synergies
between Databases and Constraint Processing. The depth and rigor
at which advanced topics are addressed (e.g., advanced consistency
methods, tree decomposition techniques, and temporal reasoning
networks) are a remarkable achievement, possible only given the wealth
and significance of the author's own contributions to the field.
This is one of those rare books you will enjoy reading over and over
again, every time acquiring new knowledge.
2 von 2 Kunden fanden die folgende Rezension hilfreich
a good introduction to constraint processing
18. Mai 2010
Format:Gebundene Ausgabe
I consider this book to be a very good place to begin one's study of constraint processing and programming.
Chapters 1-7 cover the essential ideas and issues behind constraint problems. Regardless of what approach
one favors towards solving such problems, the definitions and algorithms provided in these chapters provide
a basis for understanding the different approaches. For the most part,
I found the book well written, and it provided many good examples that helped clarify a definition and/or algorithm.
However, I do have a few criticisms. The main criticism is that the book seems biased towards problems (and hence
algorithms for solving them) whose constraints can be enumerated as a set of tuples over sets having
small finite domains (if the domains are not small, the algorithms become impractical due to time and space complexity).
Such constraints are in fact a small subset of the types of constraints that one may encounter in practice. In practice,
domains sets might be very large (or even infinite!) and people (i.e. scientists, engineers, and business people) tend to
express constraints by using formulas that may not translate so readily into sets of tuples. Thus, if the intent is to use
the information in this book as the basis for establishing a constraint-programming system, then one will have to place
limitations on both the kinds of solvable problems, and how the constraints of the problem can be expressed.
The other main criticism is that there is very little discussion or exposure to stochastic and statistical methods, aside from
the brief introduction to stochastic local search in Chapter 7. I suppose one could have written a similar introductory book in which Monte Carlo methods and other stochastic techniques had center stage. In my opinion, such techniques are necessary to help alleviate the first criticism.
Finally, I would have appreciated a bit more variety in terms of the examples provided. The author received much mileage out of
a few graph-coloring examples, but for some exercises at the end of the chapter, these referred-to examples did not have enough
complexity to illustrate the lesson of the exercise.
However, despite these criticisms, I still give the book four stars, because it is generally well-written with good foundational information, and, to my knowledge, there currently is not a better book on the market.
Chapters 1-7 cover the essential ideas and issues behind constraint problems. Regardless of what approach
one favors towards solving such problems, the definitions and algorithms provided in these chapters provide
a basis for understanding the different approaches. For the most part,
I found the book well written, and it provided many good examples that helped clarify a definition and/or algorithm.
However, I do have a few criticisms. The main criticism is that the book seems biased towards problems (and hence
algorithms for solving them) whose constraints can be enumerated as a set of tuples over sets having
small finite domains (if the domains are not small, the algorithms become impractical due to time and space complexity).
Such constraints are in fact a small subset of the types of constraints that one may encounter in practice. In practice,
domains sets might be very large (or even infinite!) and people (i.e. scientists, engineers, and business people) tend to
express constraints by using formulas that may not translate so readily into sets of tuples. Thus, if the intent is to use
the information in this book as the basis for establishing a constraint-programming system, then one will have to place
limitations on both the kinds of solvable problems, and how the constraints of the problem can be expressed.
The other main criticism is that there is very little discussion or exposure to stochastic and statistical methods, aside from
the brief introduction to stochastic local search in Chapter 7. I suppose one could have written a similar introductory book in which Monte Carlo methods and other stochastic techniques had center stage. In my opinion, such techniques are necessary to help alleviate the first criticism.
Finally, I would have appreciated a bit more variety in terms of the examples provided. The author received much mileage out of
a few graph-coloring examples, but for some exercises at the end of the chapter, these referred-to examples did not have enough
complexity to illustrate the lesson of the exercise.
However, despite these criticisms, I still give the book four stars, because it is generally well-written with good foundational information, and, to my knowledge, there currently is not a better book on the market.
2 von 2 Kunden fanden die folgende Rezension hilfreich
The best reference on Constraints Processing
11. September 2007
Format:Gebundene Ausgabe
This is the most comprehensive book in the area of Constraint Processing (aka Constraint Solving and CSP) I have seen. It starts with the basics and takes the reader all the way to advanced topics. It is an excellent place to start if you want to learn the field. It is also an excellent reference for researchers and practitioners. I use this book frequently in my research and my work in the field of Formal Verification. The book is also of great value to those in Artificial Intelligence, Optimization, and Operation Research.
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