Matches in SemOpenAlex for { <https://semopenalex.org/work/W1949971604> ?p ?o ?g. }
Showing items 1 to 57 of
57
with 100 items per page.
- W1949971604 abstract "Cellular encoding is a method for encoding a family of neural networks into a set of labeled trees. Such sets of trees can be evolved by the genetic algorithm so as to find a particular set of trees that encodes a family of Boolean neural networks for computing a family of Boolean functions. Cellular encoding is presented as a graph grammar. A method is proposed for translating a cellular encoding into a set of graph grammar rewriting rules of the kind used in the 'Berlin' algebraic approach to graph rewriting. The genetic search of neural networks via cellular encoding appears as a grammatical inference process where the language to parse is implicitly specified, instead of explicitly by positive and negative examples. Experimental results shows that the genetic algorithm can infer grammars that derive neural networks for the parity, symmetry and decoder Boolean function of arbitrary large size. >" @default.
- W1949971604 created "2016-06-24" @default.
- W1949971604 creator A5027697131 @default.
- W1949971604 date "1993-04-22" @default.
- W1949971604 modified "2023-10-18" @default.
- W1949971604 title "Cellular encoding as a graph grammar" @default.
- W1949971604 hasPublicationYear "1993" @default.
- W1949971604 type Work @default.
- W1949971604 sameAs 1949971604 @default.
- W1949971604 citedByCount "7" @default.
- W1949971604 countsByYear W19499716042012 @default.
- W1949971604 countsByYear W19499716042021 @default.
- W1949971604 crossrefType "journal-article" @default.
- W1949971604 hasAuthorship W1949971604A5027697131 @default.
- W1949971604 hasConcept C118615104 @default.
- W1949971604 hasConcept C125411270 @default.
- W1949971604 hasConcept C154945302 @default.
- W1949971604 hasConcept C33923547 @default.
- W1949971604 hasConcept C41008148 @default.
- W1949971604 hasConcept C53893814 @default.
- W1949971604 hasConcept C56601403 @default.
- W1949971604 hasConcept C80444323 @default.
- W1949971604 hasConceptScore W1949971604C118615104 @default.
- W1949971604 hasConceptScore W1949971604C125411270 @default.
- W1949971604 hasConceptScore W1949971604C154945302 @default.
- W1949971604 hasConceptScore W1949971604C33923547 @default.
- W1949971604 hasConceptScore W1949971604C41008148 @default.
- W1949971604 hasConceptScore W1949971604C53893814 @default.
- W1949971604 hasConceptScore W1949971604C56601403 @default.
- W1949971604 hasConceptScore W1949971604C80444323 @default.
- W1949971604 hasLocation W19499716041 @default.
- W1949971604 hasOpenAccess W1949971604 @default.
- W1949971604 hasPrimaryLocation W19499716041 @default.
- W1949971604 hasRelatedWork W1008627309 @default.
- W1949971604 hasRelatedWork W1505160416 @default.
- W1949971604 hasRelatedWork W1512742637 @default.
- W1949971604 hasRelatedWork W1513152267 @default.
- W1949971604 hasRelatedWork W1515279303 @default.
- W1949971604 hasRelatedWork W1522194571 @default.
- W1949971604 hasRelatedWork W1534278863 @default.
- W1949971604 hasRelatedWork W1534696515 @default.
- W1949971604 hasRelatedWork W1576818901 @default.
- W1949971604 hasRelatedWork W1647980702 @default.
- W1949971604 hasRelatedWork W2071174191 @default.
- W1949971604 hasRelatedWork W2081456352 @default.
- W1949971604 hasRelatedWork W2111935653 @default.
- W1949971604 hasRelatedWork W2116827947 @default.
- W1949971604 hasRelatedWork W2145752261 @default.
- W1949971604 hasRelatedWork W2246837390 @default.
- W1949971604 hasRelatedWork W270546983 @default.
- W1949971604 hasRelatedWork W2968447125 @default.
- W1949971604 hasRelatedWork W3003512226 @default.
- W1949971604 hasRelatedWork W3005022890 @default.
- W1949971604 isParatext "false" @default.
- W1949971604 isRetracted "false" @default.
- W1949971604 magId "1949971604" @default.
- W1949971604 workType "article" @default.