Thu, 21 Aug 2008 10:12:31 BST CiteULike: woutervdb constraint http://www.citeulike.org/user/woutervdb/tag/constraint CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/woutervdb/article/1196366 <i>No. 1106. (1996), pp. 265-280.</i><br /><br />Many real-life Constraint Satisfaction Problems are over-constrained. In order to provide some kind of solution for such problems, this paper proposes a constraint relaxation mechanism fully integrated with the constraint solver. Such a constraint relaxation system must be able to perform two fundamental tasks: identification of constraints to relax and efficient constraint suppression. Assumption-based Truth Maintenance Systems propose a uniform framework to tackle those requirements. The main ... Implementing Constraint Relaxation over Finite Domains using ATMS Narendra Jussien Patrice Boizumault No. 1106. (1996), pp. 265-280. 2007-03-29T15:35:12-00:00 1996 1106 265 280 Springer-Verlag atms constraint csp relaxation http://www.citeulike.org/user/woutervdb/article/1186093 <i>(1992)</i><br /><br />Arc consistency algorithms are used in solving constraint satisfaction problems and are important in constraint logic programming languages. Search order heuristics for arc consistency algorithms significantly enhance the efficiency of their implementation. In this paper we propose and evaluate several ordering heuristics. Care is taken with experimental design, involving random problems, and statistical evaluation of results. A heuristic is identified which yields about 50% savings on ... Ordering heuristics for arc consistency algorithms R Wallace E Freuder (1992) 2007-03-25T13:51:49-00:00 1992 constraint csp heuristics http://www.citeulike.org/user/woutervdb/article/1180928 <i>Artificial Intelligence, Vol. 57, No. 2--3. (1992), pp. 291-321.</i><br /><br />Consistency techniques have been studied extensively in the past as a way of tackling constraint satisfaction problems (CSP). In particular, various arc-consistency algorithms have been proposed, originating from Waltz's filtering algorithm [26] and culminating in the optimal algorithm AC-4 of Mohr and Henderson [15]. AC-4 runs in O(ed 2 ) in the worst case, where e is the number of arcs (or constraints) and d is the size of the largest domain. Being applicable to the whole class of (binary)... A Generic Arc-Consistency Algorithm and its Specializations Pascal Van Hentenryck Yves Deville Choh Teng Artificial Intelligence, Vol. 57, No. 2--3. (1992), pp. 291-321. 2007-03-22T17:23:34-00:00 1992 Artificial Intelligence 57 2--3 291 321 ac-4 arc-consistency constraint csp generic propagation satisfaction http://www.citeulike.org/user/woutervdb/article/1172056 <i>Lecture Notes in Computer Science, Vol. 1864 (2000), pp. 271-??.</i><br /><br />) Jeremy Frank ? Ari K. J'onsson ?? Paul Morris ?? NASA Ames Research Center Mail Stop 269-1 Moffett Field, CA 94035 ffrank,jonsson,pmorrisg@ptolemy.arc.nasa.gov Abstract. In recent years, researchers have reformulated STRIPS planning problems as SAT problems or CSPs. In this paper, we discuss the Constraint-Based Interval Planning (CBIP) paradigm, which can represent planning problems incorporating interval time and resources. We describe how to reformulate mutual exclusion... On Reformulating Planning as Dynamic Constraint Satisfaction Jeremy Frank Ari Jonsson Paul Morris Lecture Notes in Computer Science, Vol. 1864 (2000), pp. 271-??. 2007-03-18T20:26:45-00:00 2000 Lecture Notes in Computer Science 1864 271 ?? constraint constraints csp planning procedural http://www.citeulike.org/user/woutervdb/article/423562 <i>(22 May 2003)</i><br /><br />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. <br><br>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.<br><br>·Examines the basic practical aspects of each topic and then tackles more advanced issues, including current research challenges<br>·Builds the reader's understanding with definitions, examples, theory, algorithms and complexity analysis<br>·Synthesizes three decades of researchers work on constraint processing in AI, databases and programming languages, operations research, management science, and applied mathematics Constraint Processing (The Morgan Kaufmann Series in Artificial Intelligence) Rina Dechter (22 May 2003) 2005-12-06T18:41:31-00:00 2003 Morgan Kaufmann constraint csp