Name
Abstract | ||
|---|---|---|
Search algorithms for solving Numeric CSPs (Constraint Satisfaction Problems) make an extensive use of filtering techniques. In this paper we show how those filtering techniques can be accelerated by discovering and exploiting some regularities during the filtering process. Two kinds of regularities are discussed, cyclic phenomena in the propagation queue and numeric regularities of the domains of the variables. We also present in this paper an attempt to unify numeric CSPs solving methods from two distinct communities, that of CSP in artificial intelligence, and that of interval analysis. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1016/S0004-3702(02)00194-7 | Artif. Intell. |
Keywords | Field | DocType |
numeric csps,strong consistency,acceleration methods,numeric constraint satisfaction problem,propagation queue,filtering techniques,numeric regularity,search algorithm,extrapolation methods,interval analysis,extensive use,artificial intelligence,distinct community,nonlinear equations,pruning,constraint satisfaction problems,interval arithmetic,propagation,cyclic phenomenon,nonlinear equation,artificial intelligent,constraint satisfaction problem | Search algorithm,Nonlinear system,Queue,Filter (signal processing),Theoretical computer science,Constraint satisfaction problem,Artificial intelligence,Interval arithmetic,Strong consistency,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
139 | 1 | 0004-3702 |
Citations | PageRank | References |
14 | 0.98 | 18 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yahia Lebbah | 1 | 115 | 19.34 |
| Olivier Lhomme | 2 | 386 | 28.48 |