SUNNY: a Lazy Portfolio Approach for Constraint Solving
Authors: Roberto Amadini, Maurizio Gabbrielli and Jacopo Mauro
Paper Information
| Title: | SUNNY: a Lazy Portfolio Approach for Constraint Solving |
| Authors: | Roberto Amadini, Maurizio Gabbrielli and Jacopo Mauro |
| Proceedings: | ICLP 2014 VSL proceedings |
| Editors: | Michael Leuschel, Tom Schrijvers and Martin Gebser |
| Keywords: | Algorithms Portfolio, Artificial Intelligence, Constraint Satisfaction, Machine Learning |
| Abstract: | ABSTRACT. 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 performances reached by SUNNY w.r.t. 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 performances of sunny-csp conform 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. |
| Pages: | 14 |
| Talk: | Jul 22 11:30 |
| Paper: | ![]() |
