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  • Towards Fewer Parameters for SAT Clause Weighting Algorithms

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    Author(s)
    Thornton, J
    Pullan, W
    Terry, J
    Griffith University Author(s)
    Pullan, Wayne J.
    Year published
    2002
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    Abstract
    Considerable progress has recently been made in using clause weighting algorithms such as DLM and SDF to solve SAT benchmark problems. While these algorithms have outperformed earlier stochastic techniques on many larger problems, this improvement has been bought at the cost of extra parameters and the complexity of fine tuning these parameters to obtain optimal run-time performance. This paper examines the use of parameters, specifically in relation to DLM, to identify underlying features in clause weighting that can be used to eliminate or predict workable parameter settings. To this end we propose and empirically evaluate ...
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    Considerable progress has recently been made in using clause weighting algorithms such as DLM and SDF to solve SAT benchmark problems. While these algorithms have outperformed earlier stochastic techniques on many larger problems, this improvement has been bought at the cost of extra parameters and the complexity of fine tuning these parameters to obtain optimal run-time performance. This paper examines the use of parameters, specifically in relation to DLM, to identify underlying features in clause weighting that can be used to eliminate or predict workable parameter settings. To this end we propose and empirically evaluate a simplified clause weighting algorithm that replaces the tabu list and flat moves parameter used in DLM. From this we show that our simplified clause weighting algorithm is competitive with DLM on the four categories of SAT problem for whichDLMhas already been optimised.
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    Conference Title
    Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
    Volume
    2557
    DOI
    https://doi.org/10.1007/3-540-36187-1_50
    Copyright Statement
    © 2002 Springer-Verlag. 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
    Publication URI
    http://hdl.handle.net/10072/1466
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    • Conference outputs

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