Please use this identifier to cite or link to this item: https://doi.org/10.1007/s10462-004-4329-2
DC FieldValue
dc.titleCounting for satisfiability by inverting resolution
dc.contributor.authorAndrei, S.
dc.date.accessioned2014-12-02T08:39:03Z
dc.date.available2014-12-02T08:39:03Z
dc.date.issued2004-12
dc.identifier.citationAndrei, S. (2004-12). Counting for satisfiability by inverting resolution. Artificial Intelligence Review 22 (4) : 339-366. ScholarBank@NUS Repository. https://doi.org/10.1007/s10462-004-4329-2
dc.identifier.issn02692821
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/114631
dc.description.abstractWe present a new algorithm for counting truth assignments of a clausal formula using inverse prepositional resolution and its associated normalization rules. The idea is opposite of the classical resolution, and is achieved by constructing in a bottom-up manner a computation graph. This means that we successively add complementary literals to generate new bigger clauses instead of solving them. Next, we make a comparison between the classical and inverse resolution, followed by a new algorithm which combines these two techniques for solving the SAT problem.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/s10462-004-4329-2
dc.sourceScopus
dc.subjectAlgorithms
dc.subjectCounting truth assignments
dc.subjectSatisfiability
dc.typeArticle
dc.contributor.departmentSINGAPORE-MIT ALLIANCE
dc.description.doi10.1007/s10462-004-4329-2
dc.description.sourcetitleArtificial Intelligence Review
dc.description.volume22
dc.description.issue4
dc.description.page339-366
dc.description.codenAIRVE
dc.identifier.isiut000225323000003
Appears in Collections:Staff Publications

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