Kangaroo: An Efficient Constraint-Based Local Search System Using Lazy Propagation

  • M. A. Hakim Newton
  • Duc Nghia Pham
  • Abdul Sattar
  • Michael Maher
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6876)

Abstract

In this paper, we introduce Kangaroo, a constraint-based local search system. While existing systems such as Comet maintain invariants after every move, Kangaroo adopts a lazy strategy, updating invariants only when they are needed. Our empirical evaluation shows that Kangaroo consistently has a smaller memory footprint than Comet, and is usually significantly faster.

Keywords

Local Search Problem Instance Partial Assignment Candidate Parameter Commit Assignment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • M. A. Hakim Newton
    • 1
    • 2
  • Duc Nghia Pham
    • 1
    • 2
  • Abdul Sattar
    • 1
    • 2
  • Michael Maher
    • 1
    • 3
    • 4
  1. 1.National ICT Australia (NICTA) Ltd.Australia
  2. 2.Institute for Integrated and Intelligent SystemsGriffith UniversityAustralia
  3. 3.School of Computer Science and EngineeringUniversity of New South WalesAustralia
  4. 4.Reasoning Research InstituteSydneyAustralia

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