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Australasian Joint Conference on Artificial Intelligence

AI 2016: AI 2016: Advances in Artificial Intelligence pp 281–287Cite as

Assignment Precipitation in Fail First Search

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9992))

Abstract

Within a fail first search, we relocate assignments towards the bottom of the upward-growing assignment stack. We do that when the related variables, due to search dynamics, become more constrained than were anticipated before. This fixes early variable selection mistakes.

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Acknowledgment

This work was partly supported by ARC Grant DP150101618.

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Authors and Affiliations

  1. IIIS, Griffith University, Nathan, Australia

    Majid Namazi, Nina G. Ghooshchi, M. A. Hakim Newton & Abdul Sattar

  2. Data61, CSIRO, Spring Hill, Australia

    Nina G. Ghooshchi & Abdul Sattar

Authors
  1. Majid Namazi
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  2. Nina G. Ghooshchi
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  3. M. A. Hakim Newton
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  4. Abdul Sattar
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Corresponding author

Correspondence to M. A. Hakim Newton .

Editor information

Editors and Affiliations

  1. University of Tasmania, Hobart, Australia

    Byeong Ho Kang

  2. Auckland University of Technology, Auckland, New Zealand

    Quan Bai

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© 2016 Springer International Publishing AG

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Namazi, M., G. Ghooshchi, N., Newton, M.A.H., Sattar, A. (2016). Assignment Precipitation in Fail First Search. In: Kang, B.H., Bai, Q. (eds) AI 2016: Advances in Artificial Intelligence. AI 2016. Lecture Notes in Computer Science(), vol 9992. Springer, Cham. https://doi.org/10.1007/978-3-319-50127-7_23

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  • DOI: https://doi.org/10.1007/978-3-319-50127-7_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50126-0

  • Online ISBN: 978-3-319-50127-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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