Open AccessBook
Constraint Processing
TLDR
Rina Dechter synthesizes three decades of researchers work on constraint processing in AI, databases and programming languages, operations research, management science, and applied mathematics to provide the first comprehensive examination of the theory that underlies constraint processing algorithms.Abstract:
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.
·Examines the basic practical aspects of each topic and then tackles more advanced issues, including current research challenges
·Builds the reader's understanding with definitions, examples, theory, algorithms and complexity analysis
·Synthesizes three decades of researchers work on constraint processing in AI, databases and programming languages, operations research, management science, and applied mathematics
Table of Contents
Preface; Introduction; Constraint Networks; Consistency-Enforcing Algorithms: Constraint Propagation; Directional Consistency; General Search Strategies; General Search Strategies: Look-Back; Local Search Algorithms; Advanced Consistency Methods; Tree-Decomposition Methods; Hybrid of Search and Inference: Time-Space Trade-offs; Tractable Constraint Languages; Temporal Constraint Networks; Constraint Optimization; Probabilistic Networks; Constraint Logic Programming; Bibliographyread more
Citations
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Book ChapterDOI
AND/OR branch-and-bound search for pure 0/1 integer linear programming problems
Radu Marinescu,Rina Dechter +1 more
TL;DR: This paper introduces a new dynamic AND/OR Branch-and-Bound algorithm able to accommodate variable ordering heuristics and demonstrates the effectiveness of the dynamic And/OR approach on a variety of benchmarks for pure 0/1 integer programming.
Proceedings ArticleDOI
Controlled propagation in continuous numerical constraint networks
TL;DR: It is shown here that this algorithm implements a strategy to enforce on a continuous constraint a consistency akin to directional bounds consistency as introduced by Dechter and Pearl for discrete problems.
Dissertation
Dynamic Service Generation: Agent interactions for service exchange on the Grid
TL;DR: Cette these propose une reflexion sur la notion de service and introduit le concept of Generation Dynamique de Service (GDS) comme une approche differente de l'echange de service en informatique, dans laquelle des services sont dynamiquement construits, fournis and utilises par des agents (humains ou artificiels).
Journal ArticleDOI
Integer and constraint programming model formulations for flight-gate assignment problem
TL;DR: This study proposes two different integer programming models, namely, timetabling and assignment based models, and then a scheduling based constraint programming model to solve the flight-gate assignment problem to optimality.
Proceedings Article
An interactive constraint-based approach to minesweeper
TL;DR: A Java applet that uses Constraint Processing (CP) to assist a human in playing the popular game Minesweeper, to illustrate the power of CP techniques to model and solve combinatorial problems in a context accessible to the general public.
References
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Journal ArticleDOI
Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Book
Computers and Intractability: A Guide to the Theory of NP-Completeness
TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
Book
Introduction to Algorithms
TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
Book
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
TL;DR: Probabilistic Reasoning in Intelligent Systems as mentioned in this paper is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty, and provides a coherent explication of probability as a language for reasoning with partial belief.