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Evolutionary-estimated programming the Turing machine by differential evolution

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dc.title Evolutionary-estimated programming the Turing machine by differential evolution en
dc.contributor.author Kouřil, Lukáš
dc.contributor.author Zelinka, Ivan
dc.relation.ispartof MENDEL 2010
dc.identifier.issn 1803-3814 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-80-214-4120-0
dc.date.issued 2010
dc.citation.spage 41
dc.citation.epage 48
dc.event.title 16th International Conference on Soft Computing MENDEL 2010
dc.event.location Brno
utb.event.state-en Czech Republic
utb.event.state-cs Česká republika
dc.event.sdate 2010-06-23
dc.event.edate 2010-06-25
dc.type conferenceObject
dc.language.iso en
dc.publisher Vysoké učení technické v Brně cs
dc.subject Turing machine en
dc.subject artificial intelligence en
dc.subject evolutionary algorithms en
dc.subject differential evolution en
dc.subject programming en
dc.subject designing rules en
dc.description.abstract This research deals with employing an artificial intelligence at estimating the rules for programming the Turing machine. The aim of this project is to simplify a programming process, which consists of designing the Turing machine's transition function. This is realized by using artificial intelligence for performing composition of the rules which map responses of the transition function in dependence on its arguments. Within the research, there were chosen a few of suitable artificial intelligence algorithms for solving this problem. In the previous working on this project, Self-Organizing Migrating Algorithm had been used. As another, there was chosen Differential Evolution as the suitable artificial intelligence algorithm for solving this problem. In this paper there is described an employment of the latter algorithm at estimating the rules for programming the Turing machines. This paper subsequently proves that the evolution can produce valid rules for solving concrete tasks by the Turing machine. This research has confirmed possibilities of simplifying programming the Turing machine by artificial intelligence. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1001753
utb.identifier.rivid RIV/70883521:28140/10:63509007!RIV11-MSM-28140___
utb.identifier.obdid 43863884
utb.identifier.scopus 2-s2.0-84904180369
utb.identifier.wok 000288144100007
utb.source d-wok
dc.date.accessioned 2011-08-09T07:33:48Z
dc.date.available 2011-08-09T07:33:48Z
utb.contributor.internalauthor Kouřil, Lukáš
utb.contributor.internalauthor Zelinka, Ivan
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