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arXiv:1909.08243cs.AI

Quantified Constraint Handling Rules

Vincent Barichard, Igor Stéphan

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Abstract

We shift the QCSP (Quantified Constraint Satisfaction Problems) framework to the QCHR (Quantified Constraint Handling Rules) framework by enabling dynamic binder and access to user-defined constraints. QCSP offers a natural framework to express PSPACE problems as finite two-players games. But to define a QCSP model, the binder must be formerly known and cannot be built dynamically even if the worst case won't occur. To overcome this issue, we define the new QCHR formalism that allows to build the binder dynamically during the solving. Our QCHR models exhibit state-of-the-art performances on static binder and outperforms previous QCSP approaches when the binder is dynamic.

arXiv comments
In Proceedings ICLP 2019, arXiv:1909.07646
Journal reference
EPTCS 306, 2019, pp. 210-223
DOI
doi:10.4204/EPTCS.306.25
Subjects
cs.AIArtificial Intelligence cs.PLProgramming Languages

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