claspfolio 2

claspfolio 2: advances in algorithm selection for answer set programming. Building on the award-winning, portfolio-based ASP solver claspfolio, we present claspfolio 2, a modular and open solver architecture that integrates several different portfolio-based algorithm selection approaches and techniques. The claspfolio 2 solver framework supports various feature generators, solver selection approaches, solver portfolios, as well as solver-schedule-based pre-solving techniques. The default configuration of claspfolio 2 relies on a light-weight version of the ASP solver clasp to generate static and dynamic instance features. The flexible open design of claspfolio 2 is a distinguishing factor even beyond ASP. As such, it provides a unique framework for comparing and combining existing portfolio-based algorithm selection approaches and techniques in a single, unified framework. Taking advantage of this, we conducted an extensive experimental study to assess the impact of different feature sets, selection approaches and base solver portfolios. In addition to gaining substantial insights into the utility of the various approaches and techniques, we identified a default configuration of claspfolio 2 that achieves substantial performance gains not only over clasp’s default configuration and the earlier version of claspfolio, but also over manually tuned configurations of clasp.

References in zbMATH (referenced in 11 articles , 1 standard article )

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  1. Amadini, Roberto; Gange, Graeme; Schachte, Peter; Søndergaard, Harald; Stuckey, Peter J.: Algorithm selection for dynamic symbolic execution: a preliminary study (2021)
  2. Sioutis, Michael; Wolter, Diedrich: Dynamic branching in qualitative constraint-based reasoning via counting local models (2021)
  3. Calimeri, Francesco; Dodaro, Carmine; Fuscà, Davide; Perri, Simona; Zangari, Jessica: Technical note. Efficiently coupling the (\mathscrI)-DLV grounder with ASP solvers (2020)
  4. Lindauer, Marius; van Rijn, Jan N.; Kotthoff, Lars: The algorithm selection competitions 2015 and 2017 (2019)
  5. Ślażyński, Mateusz: Research report on automatic synthesis of local search neighborhood operators (2019)
  6. Taupe, Richard; Schekotihin, Konstantin; Schüller, Peter; Weinzierl, Antonius; Friedrich, Gerhard: Exploiting partial knowledge in declarative domain-specific heuristics for ASP (2019)
  7. Cerutti, Federico; Vallati, Mauro; Giacomin, Massimiliano: On the impact of configuration on abstract argumentation automated reasoning (2018)
  8. Eggensperger, Katharina; Lindauer, Marius; Hoos, Holger H.; Hutter, Frank; Leyton-Brown, Kevin: Efficient benchmarking of algorithm configurators via model-based surrogates (2018)
  9. Bischl, Bernd; Kerschke, Pascal; Kotthoff, Lars; Lindauer, Marius; Malitsky, Yuri; Fréchette, Alexandre; Hoos, Holger; Hutter, Frank; Leyton-Brown, Kevin; Tierney, Kevin; Vanschoren, Joaquin: ASlib: a benchmark library for algorithm selection (2016)
  10. Dodaro, Carmine; Gasteiger, Philip; Leone, Nicola; Musitsch, Benjamin; Ricca, Francesco; Shchekotykhin, Kostyantyn: Combining answer set programming and domain heuristics for solving hard industrial problems (application paper) (2016)
  11. Hoos, Holger; Lindauer, Marius; Schaub, Torsten: \textttclaspfolio2: advances in algorithm selection for answer set programming (2014)