TY - JOUR
T1 - SUNNY
T2 - A lazy portfolio approach for constraint solving
AU - Amadini, Roberto
AU - Gabbrielli, Maurizio
AU - Mauro, Jacopo
PY - 2014/7/1
Y1 - 2014/7/1
N2 - Within the context of constraint solving, a portfolio approach allows one to exploit the synergy between different solvers in order to create a globally better solver. In this paper we present SUNNY: a simple and flexible algorithm that takes advantage of a portfolio of constraint solvers in order to compute-without learning an explicit model-a schedule of them for solving a given Constraint Satisfaction Problem (CSP). Motivated by the performance reached by SUNNY vs. different simulations of other state of the art approaches, we developed sunny-csp, an effective portfolio solver that exploits the underlying SUNNY algorithm in order to solve a given CSP. Empirical tests conducted on exhaustive benchmarks of MiniZinc models show that the actual performance of sunny-csp conforms to the predictions. This is encouraging both for improving the power of CSP portfolio solvers and for trying to export them to fields such as Answer Set Programming and Constraint Logic Programming.
AB - Within the context of constraint solving, a portfolio approach allows one to exploit the synergy between different solvers in order to create a globally better solver. In this paper we present SUNNY: a simple and flexible algorithm that takes advantage of a portfolio of constraint solvers in order to compute-without learning an explicit model-a schedule of them for solving a given Constraint Satisfaction Problem (CSP). Motivated by the performance reached by SUNNY vs. different simulations of other state of the art approaches, we developed sunny-csp, an effective portfolio solver that exploits the underlying SUNNY algorithm in order to solve a given CSP. Empirical tests conducted on exhaustive benchmarks of MiniZinc models show that the actual performance of sunny-csp conforms to the predictions. This is encouraging both for improving the power of CSP portfolio solvers and for trying to export them to fields such as Answer Set Programming and Constraint Logic Programming.
KW - Algorithms Portfolio
KW - Artificial Intelligence
KW - Constraint Satisfaction
KW - Machine Learning
U2 - 10.1017/S1471068414000179
DO - 10.1017/S1471068414000179
M3 - Journal article
AN - SCOPUS:84904659641
SN - 1471-0684
VL - 14
SP - 509
EP - 524
JO - Theory and Practice of Logic Programming
JF - Theory and Practice of Logic Programming
IS - 4-5
ER -