SUNNY: a Lazy Portfolio Approach for Constraint Solving

Author:

AMADINI ROBERTO,GABBRIELLI MAURIZIO,MAURO JACOPO

Abstract

AbstractWithin 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 developedsunny-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 ofsunny-cspconforms 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.

Publisher

Cambridge University Press (CUP)

Subject

Artificial Intelligence,Computational Theory and Mathematics,Hardware and Architecture,Theoretical Computer Science,Software

Reference33 articles.

1. Hutter F. , Xu L. , Hoos H. H. , and Leyton-Brown K. 2012. Algorithm Runtime Prediction: The State of the Art. CoRR abs/1211.0906.

2. A self-adaptive multi-engine solver for quantified Boolean formulas

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