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An Efficient Solver for Parametrized Difference Revision

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AI 2019: Advances in Artificial Intelligence (AI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11919))

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Abstract

We present GenC, an efficient and highly-parallel belief revision solver for paramatrized difference operators. GenC uses an AllSAT solver to enumerate the possible models of a formula, and then determines the output of revision through a series of bit comparisons. The result is a system that can calculate the result of revision for formulas with 100 variables and millions of clauses in just seconds; the running times obtained by GenC far surpass existing solvers for belief revision. The system also has many features that are useful for practical problems: it supports both interactive and offline data entry, it allows multiple formats for entering formulas, and it provides output in human-readable format. Most importantly, GenC is able to model revision by any parametrized difference operator, which allows a wide range of practical problems to be easily captured.

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Authors and Affiliations

  1. BC Institute of Technology, Burnaby, Canada

    Aaron Hunter & John Agapeyev

Authors
  1. Aaron Hunter
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  2. John Agapeyev
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Correspondence to Aaron Hunter .

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Editors and Affiliations

  1. University of South Australia, Adelaide, SA, Australia

    Jixue Liu

  2. The University of Melbourne, Melbourne, VIC, Australia

    James Bailey

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Hunter, A., Agapeyev, J. (2019). An Efficient Solver for Parametrized Difference Revision. In: Liu, J., Bailey, J. (eds) AI 2019: Advances in Artificial Intelligence. AI 2019. Lecture Notes in Computer Science(), vol 11919. Springer, Cham. https://doi.org/10.1007/978-3-030-35288-2_12

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  • DOI: https://doi.org/10.1007/978-3-030-35288-2_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-35287-5

  • Online ISBN: 978-3-030-35288-2

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