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

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Author(s)
Newton, MAH
Pham, DN
Sattar, A
Maher, M
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Jimmy Lee

Date
2011
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346752 bytes

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Perugia, Italy

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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.

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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6876 LNCS

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© 2011 Springer Berlin / Heidelberg. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com

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Artificial intelligence not elsewhere classified

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