About: Boolean satisfiability algorithm heuristics     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : owl:Thing, within Data Space : dbpedia.demo.openlinksw.com associated with source document(s)
QRcode icon
http://dbpedia.demo.openlinksw.com/describe/?url=http%3A%2F%2Fdbpedia.org%2Fresource%2FBoolean_satisfiability_algorithm_heuristics&invfp=IFP_OFF&sas=SAME_AS_OFF

The Boolean satisfiability problem (frequently abbreviated SAT) can be stated formally as:given a Boolean expression with variables, finding an assignment of the variables such that is true. It is seen as the canonical NP-complete problem. While no efficient algorithm is known to solve this problem in the general case, there are certain heuristics, informally called 'rules of thumb' in programming, that can usually help solve the problem reasonably efficiently.

AttributesValues
rdfs:label
  • Boolean satisfiability algorithm heuristics (en)
rdfs:comment
  • The Boolean satisfiability problem (frequently abbreviated SAT) can be stated formally as:given a Boolean expression with variables, finding an assignment of the variables such that is true. It is seen as the canonical NP-complete problem. While no efficient algorithm is known to solve this problem in the general case, there are certain heuristics, informally called 'rules of thumb' in programming, that can usually help solve the problem reasonably efficiently. (en)
dcterms:subject
Wikipage page ID
Wikipage revision ID
Link from a Wikipage to another Wikipage
sameAs
dbp:wikiPageUsesTemplate
has abstract
  • The Boolean satisfiability problem (frequently abbreviated SAT) can be stated formally as:given a Boolean expression with variables, finding an assignment of the variables such that is true. It is seen as the canonical NP-complete problem. While no efficient algorithm is known to solve this problem in the general case, there are certain heuristics, informally called 'rules of thumb' in programming, that can usually help solve the problem reasonably efficiently. Although no known algorithm is known to solve SAT in polynomial time, there are classes of SAT problems which do have efficient algorithms that solve them. These classes of problems arise from many practical problems in AI planning, circuit testing, and software verification. Research on constructing efficient SAT solvers has been based on various principles such as resolution, search, local search and random walk, binary decisions, and Stalmarck's algorithm. Some of these algorithms are deterministic, while others may be stochastic. As there exist polynomial-time algorithms to convert any Boolean expression to conjunctive normal form such as Tseitin's algorithm, posing SAT problems in CNF does not change their computational difficulty. SAT problems are canonically expressed in CNF because CNF has certain properties that can help prune the search space and speed up the search process. (en)
prov:wasDerivedFrom
page length (characters) of wiki page
foaf:isPrimaryTopicOf
is foaf:primaryTopic of
Faceted Search & Find service v1.17_git139 as of Feb 29 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 08.03.3330 as of Mar 19 2024, on Linux (x86_64-generic-linux-glibc212), Single-Server Edition (378 GB total memory, 67 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software