Simple algorithm portfolio for SAT
نویسندگان
چکیده
منابع مشابه
A MAX-SAT Algorithm Portfolio
The results of the last MaxSAT Evaluations suggest there is no universal 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 o...
متن کاملSATzilla2008: an Automatic Algorithm Portfolio for SAT
Empirical studies often observe that the performance of algorithms across problem domains can be quite uncorrelated. When this occurs, it seems practical to investigate the use of algorithm portfolios that draw on the strengths of multiple algorithms. SATzilla is such an algorithm portfolio for SAT problems; it was first deployed in the 2004 SAT competition [13], and recently an updated version...
متن کاملSATzilla2009: an Automatic Algorithm Portfolio for SAT
Empirical studies often observe that the performance of algorithms across problem domains can be quite uncorrelated. When this occurs, it seems practical to investigate the use of algorithm portfolios that draw on the strengths of multiple algorithms. SATzilla is such an algorithm portfolio for SAT problems; it was first deployed in the 2004 SAT competition [12], and recently an updated version...
متن کاملSATzilla: Portfolio-based Algorithm Selection for SAT
It has been widely observed that there is no single “dominant” SAT solver; instead, different solvers perform best on different instances. Rather than following the traditional approach of choosing the best solver for a given class of instances, we advocate making this decision online on a per-instance basis. Building on previous work, we describe SATzilla, an automated approach for constructin...
متن کاملSATzilla: An Algorithm Portfolio for SAT
Inspired by the success of recent work in the constraint programming community on typical-case complexity, in [3] we developed a new methodology for using machine learning to study empirical hardness of hard problems on realistic distributions. In [2] we demonstrated that this new approach can be used to construct practical algorithm portfolios. In brief, the fact that algorithms for solving NP...
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ژورنال
عنوان ژورنال: Artificial Intelligence Review
سال: 2011
ISSN: 0269-2821,1573-7462
DOI: 10.1007/s10462-011-9290-2