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Scaling Search with Pattern Databases

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Model Checking and Artificial Intelligence (MoChArt 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5348))

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Abstract

In this paper, we illustrate efforts to perform memory efficient large-scale search. We first generate sets of disjoint symbolic pattern databases on disk. These pattern databases are then used for heuristic guidance, while applying explicit-state external-memory heuristic search. Different options for parallelization to save time and memory are presented. The general techniques are mapped to the (n 2 − 1)-puzzle as a large-scale case study.

This research was supported by the German Research Council (DFG) in the projects heuristic search, directed model checking and algorithm engineering.

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Author information

Authors and Affiliations

  1. Technische Universität Dortmund, Germany

    Stefan Edelkamp, Shahid Jabbar & Peter Kissmann

Authors
  1. Stefan Edelkamp
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  2. Shahid Jabbar
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  3. Peter Kissmann
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Bar Ilan University, 52900, Ramat Gan, Israel

    Doron A. Peled

  2. Department of Computer Science, University of Liverpool, L69 3BX, Liverpool, UK

    Michael J. Wooldridge

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© 2009 Springer-Verlag Berlin Heidelberg

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Edelkamp, S., Jabbar, S., Kissmann, P. (2009). Scaling Search with Pattern Databases. In: Peled, D.A., Wooldridge, M.J. (eds) Model Checking and Artificial Intelligence. MoChArt 2008. Lecture Notes in Computer Science(), vol 5348. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00431-5_4

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  • DOI: https://doi.org/10.1007/978-3-642-00431-5_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00430-8

  • Online ISBN: 978-3-642-00431-5

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