License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CP.2022.24
URN: urn:nbn:de:0030-drops-166534
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Gentzel, Rebecca ; Michel, Laurent ; van Hoeve, Willem-Jan

Heuristics for MDD Propagation in HADDOCK

LIPIcs-CP-2022-24.pdf (0.9 MB)


Haddock, introduced in [R. Gentzel et al., 2020], is a declarative language and architecture for the specification and the implementation of multi-valued decision diagrams. It relies on a labeled transition system to specify and compose individual constraints into a propagator with filtering capabilities that automatically deliver the expected level of filtering. Yet, the operational potency of the filtering algorithms strongly correlate with heuristics for carrying out refinements of the diagrams. This paper considers how to empower Haddock users with the ability to unobtrusively specify various such heuristics and derive the computational benefits of exerting fine-grained control over the refinement process.

BibTeX - Entry

  author =	{Gentzel, Rebecca and Michel, Laurent and van Hoeve, Willem-Jan},
  title =	{{Heuristics for MDD Propagation in HADDOCK}},
  booktitle =	{28th International Conference on Principles and Practice of Constraint Programming (CP 2022)},
  pages =	{24:1--24:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-240-2},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{235},
  editor =	{Solnon, Christine},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-166534},
  doi =		{10.4230/LIPIcs.CP.2022.24},
  annote =	{Keywords: Decision Diagrams}

Keywords: Decision Diagrams
Collection: 28th International Conference on Principles and Practice of Constraint Programming (CP 2022)
Issue Date: 2022
Date of publication: 23.07.2022
Supplementary Material: Software (Source Code):

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