Open AccessBook
Constraint Processing
Reads0
Chats0
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
More filters
Journal ArticleDOI
Multi-node graphs: a framework for multiplexed biological assays.
TL;DR: It is shown, using random multi-node graphs that the scalability of multiplex PCR is constrained by a phase transition, suggesting fundamental limits on efforts to improve the cost-effectiveness and throughput of standardmultiplex PCR assays.
Journal ArticleDOI
Epistemic graphs for representing and reasoning with positive and negative influences of arguments
TL;DR: The authors introduce epistemic graphs as a generalization of the epistemic approach to probabilistic argumentation, which can model both attack and support as well as relations that are neither support nor attack, thus providing a more finegrained alternative to the standard Dung's approaches when it comes to determining the status of a given argument.
Journal ArticleDOI
Creating Polytope Representations of Design Spaces for Visual Exploration Using Consistency Techniques
TL;DR: In this paper, a polytope-based representation is presented to geometrically approximate the design space, which is represented as a finite set of (possibly nonconvex) polytopes, i.e., points, intervals, polygons, and polyhedra.
Proceedings ArticleDOI
Constrained Optimization with Partial CP-Nets
Malek Mouhoub,Sultan Ahmed +1 more
TL;DR: A novel algorithm to find the Pareto optimal outcomes with respect to an acyclic partial CP-net and a set of hard constraints is proposed, called Search-Partial-CP, which can significantly reduce the search space by pruning every infeasible or dominated outcome.
Proceedings Article
Exploiting the structure of hierarchical plans in temporal constraint propagation
TL;DR: This paper describes a means to exploit the structure of a HTN plan in performing temporal propagation on an associated Simple Temporal Network, and results indicate an order of magnitude improvement on real-world plans.
References
More filters
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.