A navigation algorithm based on the reinforcement learning reward system and optimised with genetic algorithm

Cabezas Olivenza, Mireya; Zulueta Guerrero, Ekaitz; Azurmendi Marquínez, Iker; Fernández-Gamiz, Unai; Rico Melgosa, Danel

dc.rights.license	Attribution 4.0 International
dc.contributor.author	Cabezas Olivenza, Mireya
dc.contributor.author	Zulueta Guerrero, Ekaitz
dc.contributor.author	Azurmendi Marquínez, Iker
dc.contributor.author	Fernández-Gamiz, Unai
dc.contributor.author	Rico Melgosa, Danel
dc.date.accessioned	2026-04-20T07:20:56Z
dc.date.available	2026-04-20T07:20:56Z
dc.date.issued	2024
dc.identifier.issn	2227-7390
dc.identifier.other	https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=180213
dc.identifier.uri	https://hdl.handle.net/20.500.11984/14187
dc.format.extent	p.
dc.language.iso	eng
dc.publisher	MDPI
dc.rights	© 2024
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/
dc.subject	ODS 9 Industria, innovación e infraestructura
dc.title	A navigation algorithm based on the reinforcement learning reward system and optimised with genetic algorithm
dcterms.accessRights	http://purl.org/coar/access_right/c_abf2
dcterms.source	Mathematics
local.contributor.group	Accionamientos aplicados a la tracción y a la generación de energía eléctrica
local.description.peerreviewed	true
local.identifier.doi	https://doi.org/10.3390/math12244030
local.contributor.otherinstitution	https://ror.org/000xsnr85
local.contributor.otherinstitution	https://ror.org/00wvqgd19
local.source.details	Vol. 12 N. 24. N. art. 4030, 2024
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