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Min-Max Message Passing and Local Consistency in Constraint Networks

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AI 2017: Advances in Artificial Intelligence (AI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10400))

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Abstract

In this paper, we uncover some relationships between local consistency in constraint networks and message passing akin to belief propagation in probabilistic reasoning. We develop a new message passing algorithm, called the min-max message passing (MMMP) algorithm, for unifying the different notions of local consistency in constraint networks. In particular, we study its connection to arc consistency (AC) and path consistency. We show that AC-3 can be expressed more intuitively in the framework of message passing. We also show that the MMMP algorithm can be modified to enforce path consistency.

The research at the University of Southern California was supported by NSF under grant numbers 1409987 and 1319966.

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Notes

  1. 1.

    We note that all messages outgoing from triplet vertices need to be initialized according to Eq. (16) to ensure that Lemma 2 holds.

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Authors and Affiliations

  1. University of Southern California, Los Angeles, CA, 90089, USA

    Hong Xu, T. K. Satish Kumar & Sven Koenig

Authors
  1. Hong Xu
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  2. T. K. Satish Kumar
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  3. Sven Koenig
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Corresponding author

Correspondence to Hong Xu .

Editor information

Editors and Affiliations

  1. La Trobe University, Melbourne, Australia

    Wei Peng

  2. La Trobe Business School, La Trobe University, Bundoora, Victoria, Australia

    Damminda Alahakoon

  3. RMIT University, Melbourne, Australia

    Xiaodong Li

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Xu, H., Kumar, T.K.S., Koenig, S. (2017). Min-Max Message Passing and Local Consistency in Constraint Networks. In: Peng, W., Alahakoon, D., Li, X. (eds) AI 2017: Advances in Artificial Intelligence. AI 2017. Lecture Notes in Computer Science(), vol 10400. Springer, Cham. https://doi.org/10.1007/978-3-319-63004-5_27

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  • DOI: https://doi.org/10.1007/978-3-319-63004-5_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63003-8

  • Online ISBN: 978-3-319-63004-5

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