Learn More
  • Smiljana V, Susan L Petrovic, Epstein, Smiljana V Petrovic, Susan L Epstein, Susan Epstein@hunter Cuny Edu +3 others
  • 2008
Problem solvers have at their disposal many heuristics that may support effective search. The efficacy of these heuristics, however, varies with the problem class, and their mutual interactions may not be well understood. The long-term goal of our work is to learn how to select appropriately from among a large body of heuristics, and how to combine them(More)
make any warranty, express or implied, or assume any legal liability for the accuracy, completeness or usefulness of any information, apparatus, product or process disclosed, or represent that its use would not infringe privately owned rights. Permission to copy in whole or in part is granted for non-proot educational and research purposes, provided that(More)
We study here constraint satisfaction problems that are based on pre-defined, explicitly given finite constraints. To solve them we propose a notion of rule consistency that can be expressed in terms of rules derived from the explicit representation of the initial constraints. This notion of local consistency is weaker than arc consistency for constraints(More)
We investigate the use of cooperation between solvers in the scheme of constraint logic programming languages over the domain of non-linear polynomial constraints. Instead of using a general and often ineecient decision procedure we propose a new approach for handling these constraints by cooperating specialised solvers. Our approach requires the design of(More)
A main concern in Constraint Programming (CP) is to determine good variable and value order heuristics. However, this is known to be quite difficult as the effects on the solving process are rarely predictable. A novel solution to handle this concern is called Autonomous Search (AS), which is a special feature allowing an automatic reconfigu-ration of the(More)