AAS 390 Chapter Notes - Chapter 1: Dpll Algorithm, Two Seconds, Pearson Product-Moment Correlation Coefficient

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Satzilla2007: a new & improved algorithm portfolio for sat. Lin xu, frank hutter, holger h. hoos and kevin leyton-brown. Empirical studies often observe that the performance of algorithms across problem domains can be quite uncorre- lated. 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 rst deployed in the. Satzilla is based on empir- ical hardness models [3, 5], learned predictors that esti- mate each algorithm"s runtime on a given sat instance. Online, given an instance: compute feature values, predict each algorithm"s running time using learned runtime models, run the algorithm predicted to be fastest. Satzilla2007 includes the following six solvers: min- isat2. 0, march dl, vallst, zchaff rand, kcnfs2006, and. Saps (with the best xed parameter setting from [2]). The version submitted to the demonstration division also contains the proprietary solvers eureka and rsat. 1.

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