File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Extending EGENET with lazy constraint consistency

TitleExtending EGENET with lazy constraint consistency
Authors
Issue Date1997
Citation
Proceedings Of The International Conference On Tools With Artificial Intelligence, 1997, p. 248-257 How to Cite?
AbstractConstraint satisfaction problems (CSPs) occur widely in real-life applications such as bin-packing, planning and scheduling. EGENET, a neural network simulator based on the min-conflict heuristic, has had remarkable success in solving hard CSPs such as hard graph-colouring problems. Consistency techniques such as arc consistency have been extensively used to improve the search behaviour of complete search methods, by removing values and combinations of values that cannot take part in any solution. They are not typically used for stochastic search methods such as EGENET. In this paper we show how to efficiently incorporate consistency methods in EGENET. This improves the convergence behaviour of EGENET and also makes it able to detect insoluble CSPs. We compare the improved EGENET against the original version and versions incorporating state-of-art consistency techniques such as AC-4 or PC-4.
Persistent Identifierhttp://hdl.handle.net/10722/158228
ISSN

 

DC FieldValueLanguage
dc.contributor.authorStuckey, Peteren_US
dc.contributor.authorTam, Vincenten_US
dc.date.accessioned2012-08-08T08:58:38Z-
dc.date.available2012-08-08T08:58:38Z-
dc.date.issued1997en_US
dc.identifier.citationProceedings Of The International Conference On Tools With Artificial Intelligence, 1997, p. 248-257en_US
dc.identifier.issn1063-6730en_US
dc.identifier.urihttp://hdl.handle.net/10722/158228-
dc.description.abstractConstraint satisfaction problems (CSPs) occur widely in real-life applications such as bin-packing, planning and scheduling. EGENET, a neural network simulator based on the min-conflict heuristic, has had remarkable success in solving hard CSPs such as hard graph-colouring problems. Consistency techniques such as arc consistency have been extensively used to improve the search behaviour of complete search methods, by removing values and combinations of values that cannot take part in any solution. They are not typically used for stochastic search methods such as EGENET. In this paper we show how to efficiently incorporate consistency methods in EGENET. This improves the convergence behaviour of EGENET and also makes it able to detect insoluble CSPs. We compare the improved EGENET against the original version and versions incorporating state-of-art consistency techniques such as AC-4 or PC-4.en_US
dc.languageengen_US
dc.relation.ispartofProceedings of the International Conference on Tools with Artificial Intelligenceen_US
dc.titleExtending EGENET with lazy constraint consistencyen_US
dc.typeConference_Paperen_US
dc.identifier.emailTam, Vincent:vtam@eee.hku.hken_US
dc.identifier.authorityTam, Vincent=rp00173en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-0031364203en_US
dc.identifier.spage248en_US
dc.identifier.epage257en_US
dc.identifier.scopusauthoridStuckey, Peter=7006033659en_US
dc.identifier.scopusauthoridTam, Vincent=7005091988en_US

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats