DC Field | Value | Language |
---|---|---|
dc.contributor.author | Dragović, Branko | en |
dc.date.accessioned | 2020-12-11T13:04:44Z | - |
dc.date.available | 2020-12-11T13:04:44Z | - |
dc.date.issued | 2019-01-01 | en |
dc.identifier.issn | 03545180 | en |
dc.identifier.uri | http://researchrepository.mi.sanu.ac.rs/handle/123456789/4438 | - |
dc.description.abstract | © 2019, University of Nis. All rights reserved. Motivated by successful p-adic modeling of the genetic code, in this paper a p-adic (ultrametric) language is introduced. This language can serve as an effective and advanced constructive element of a future artificial intelligence. In this geometric approach to artificial language, we mainly use p-adic distance as the most powerful example of ultrametrics. Here p-adic distance is a tool to quantify similarity between words – similarity between their structure and similarity between their meaning. As a simple illustration, a p-adic language with four letters and their 3-letter words is presented. | en |
dc.relation.ispartof | Filomat | en |
dc.subject | P-adic artificial language | P-adic distance | P-adic similarity | en |
dc.title | Towards p-adic artificial language | en |
dc.type | Article | en |
dc.identifier.doi | 10.2298/FIL1904227D | en |
dc.identifier.scopus | 2-s2.0-85078307294 | en |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/85078307294 | en |
dc.relation.firstpage | 1227 | en |
dc.relation.lastpage | 1233 | en |
dc.contributor.orcid | #NODATA# | en |
dc.relation.issue | 4 | en |
dc.relation.volume | 33 | en |
item.cerifentitytype | Publications | - |
item.openairetype | Article | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
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