Self-configuring Cost-Sensitive Hierarchical Clustering with Recourse

  • Carlos Ansotegui
  • Meinolf Sellmann
  • Kevin TierneyEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11008)


We revisit algorithm selection for declarative programming solvers. We introduce two main ideas to improve cost-sensitive hierarchical clustering: First, to augment the portfolio builder with a self-configuration component. And second, we propose that the algorithm selector assesses the confidence level of its own prediction, so that a more defensive recourse action can be used to overturn the original recommendation.



We thank the Paderborn Center for Parallel Computation (PC\(^2\)) for the use of their high throughput cluster and Marius Lindauer for his kind help with the OASC benchmarks.


  1. 1.
    Ansotegui, C., Malitsky, Y., Samulowitz, H., Sellmann, M., Tierney, K.: Model-based genetic algorithms for algorithm configuration. In: IJCAI, pp. 733–739 (2015)Google Scholar
  2. 2.
    Bischl, B., et al.: ASlib: a benchmark library for algorithm selection. Artif. Intell. 237, 41–58 (2016)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Cameron, C., Hoos, H.H., Leyton-Brown, K., Hutter, F.: OASC-2017:* zilla submission. In: Open Algorithm Selection Challenge 2017, pp. 15–18 (2017)Google Scholar
  4. 4.
    Kadioglu, S., Malitsky, Y., Sabharwal, A., Samulowitz, H., Sellmann, M.: Algorithm selection and scheduling. In: CP, pp. 454–469 (2011)Google Scholar
  5. 5.
    Leyton-Brown, K., Nudelman, E., Andrew, G., McFadden, J., Shoham, Y.: A portfolio approach to algorithm selection. In: IJCAI, pp. 1542–1543 (2003)Google Scholar
  6. 6.
    Leyton-Brown, K., Nudelman, E., Shoham, Y.: Empirical hardness models: methodology and a case study on combinatorial auctions. J. ACM (JACM) 56(4), 22 (2009)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Lindauer, M., van Rijn, J., Kotthoff, L.: Open algorithm selection challenge 2017: setup and scenarios. In: Open Algorithm Selection Challenge 2017, pp. 1–7 (2017)Google Scholar
  8. 8.
    Lindauer, M., van Rijn, J.N., Kotthoff, L.: The Algorithm Selection Competition Series 2015–17. ArXiv e-prints, May 2018Google Scholar
  9. 9.
    Lindauer, M., Hutter, F., Hoos, H.H., Schaub, T.: AutoFolio: an automatically configured algorithm selector (extended abstract). In: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, Melbourne, Australia, 19–25 August 2017, pp. 5025–5029 (2017)Google Scholar
  10. 10.
    Liu, T., Amadini, R., Mauro, J.: Sunny with algorithm configuration. In: Open Algorithm Selection Challenge 2017, pp. 12–14 (2017)Google Scholar
  11. 11.
    Malitsky, Y., Sabharwal, A., Samulowitz, H., Sellmann, M.: Algorithm portfolios based on cost-sensitive hierarchical clustering. In: IJCAI, pp. 608–614 (2013)Google Scholar
  12. 12.
    Malitsky, Y., Sabharwal, A., Samulowitz, H., Sellmann, M.: Boosting sequential solver portfolios: knowledge sharing and accuracy prediction. In: 7th International Conference on Learning and Intelligent Optimization, LION 7, Catania, Italy, pp. 153–167 (2013)Google Scholar
  13. 13.
    O’Mahony, E., Hebrard, E., Holland, A., Nugent, C., O’Sullivan, B.: Using case-based reasoning in an algorithm portfolio for constraint solving. In: Irish Conference on Artificial Intelligence and Cognitive Science (2008)Google Scholar
  14. 14.
    Xu, L., Hutter, F., Hoos, H., Leyton-Brown, K.: SATzilla: portfolio-based algorithm selection for sat. JAIR 32(1), 565–606 (2008)CrossRefGoogle Scholar
  15. 15.
    Xu, L., Hutter, F., Shen, J., Hoos, H., Leyton-Brown, K.: SATzilla2012: improved algorithm selection based on cost-sensitive classification models. In: SAT Competition (2012)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Carlos Ansotegui
    • 1
  • Meinolf Sellmann
    • 2
  • Kevin Tierney
    • 3
    Email author
  1. 1.University of LleidaLleidaSpain
  2. 2.General Electric, Global Research CenterNiskayunaUSA
  3. 3.Bielefeld UniversityBielefeldGermany

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