SUNNY: a Lazy Portfolio Approach for Constraint Solving

被引:32
作者
Amadini, Roberto [1 ]
Gabbrielli, Maurizio [1 ]
Mauro, Jacopo [1 ]
机构
[1] Univ Bologna, Dept Comp Sci & Engn, Lab Focus INRIA, I-40126 Bologna, Italy
关键词
Algorithms Portfolio; Artificial Intelligence; Constraint Satisfaction; Machine Learning; MULTI-ENGINE SOLVER;
D O I
10.1017/S1471068414000179
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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.
引用
收藏
页码:509 / 524
页数:16
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