Name
Abstract | ||
|---|---|---|
The results of the last MaxSAT Evaluations suggest there is no uni- versal best algorithm for solving MaxSAT, as the fastest solver often depends on the type of instance. Having an oracle able to predict the most suitable MaxSAT solver for a given instance would result in the most robust solver. Inspired by the success of SATzilla for SAT, this paper describes the first approach for a portfolio of alg orithms for MaxSAT. Compared to existing solvers, the resulting portfolio can achieve significant performance improvements on a repre senta- tive set of instances. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.3233/978-1-58603-891-5-911 | European Conference on Artificial Intelligence |
Keywords | Field | DocType |
fastest solver,robust solver,universal best algorithm,suitable maxsat solver,significant performance improvement,last maxsat evaluations,max-sat algorithm portfolio,resulting portfolio | Maximum satisfiability problem,Mathematical optimization,Computer science,Oracle,Algorithm,Portfolio,Artificial intelligence,Solver,Machine learning | Conference |
Volume | ISSN | Citations |
178 | 0922-6389 | 4 |
PageRank | References | Authors |
0.39 | 11 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paulo J. Matos | 1 | 16 | 1.79 |
| Jordi Planes | 2 | 486 | 31.38 |
| Florian Letombe | 3 | 48 | 4.46 |
| Joao Marques-Silva | 4 | 1947 | 124.04 |