An extensible autonomous search framework for constraint programming
Autor
Crawford B.
Soto R.
Castro C.
Monfroy E.
Paredes F.
Resumen
Constraint programming is a modern programming paradigm devoted to solve constraint-based problems, in particular combinatorial problems. In this paradigm, the efficiency on the solving process is the key, which generally depends on the selection of suitable search strategies. However, determining a good search strategy is quite difficult, as its effects on the solving process are hard to predict. A novel solution to handle this concern is called autonomous search, which is a special feature allowing an automatic reconfiguration of the solving process when a poor performance is detected. In this paper, we present an extensible architecture for performing autonomous search in a constraint programming context. The idea is to carry out an "on the fly" replacement of bad-performing strategies by more promising ones. We report encouraging results where the use of autonomous search in the resolution outperforms the use of individual strategies. © 2011 Academic Journals.
Colecciones
Ítems relacionados
Mostrando ítems relacionados por Título, autor o materia.
-
Article
Using autonomous search for solving constraint satisfaction problems via new modern approaches (2020)
Soto R.; Crawford B.; Olivares R.; Galleguillos C.; Castro C.; Johnson F.; Paredes F.; Norero E. (Elsevier B.V., 2016) -
Article
A reactive and hybrid constraint solver (2020)
Monfroy E.; Castro C.; Crawford B.; Soto R.; Paredes F.; Figueroa C. (2013) -
Article
Choice functions for autonomous search in constraint programming: GA vs. PSO [Funkcije izbora za samostalno pretraživanje u ograničenom programiranju: Genetski algoritam nasuprot optimizaciji roja čestica] (2020)
Soto R.; Crawford B.; Misra S.; Palma W.; Monfroy E.; Castro C.; Paredes F. (2013)