Optimal navigation of a smart active particle: directional and distance sensing

dc.contributor.authorPutzke, Mischa
dc.contributor.authorStark, Holger
dc.contributor.otherSpringer
dc.date.accessioned2023-11-17T13:32:48Z
dc.date.available2023-11-17T13:32:48Z
dc.date.issued2023-06
dc.description.abstractWe employ Q learning, a variant of reinforcement learning, so that an active particle learns by itself to navigate on the fastest path toward a target while experiencing external forces and flow fields. As state variables, we use the distance and direction toward the target, and as action variables the active particle can choose a new orientation along which it moves with constant velocity. We explicitly investigate optimal navigation in a potential barrier/well and a uniform/ Poiseuille/swirling flow field. We show that Q learning is able to identify the fastest path and discuss the results. We also demonstrate that Q learning and applying the learned policy works when the particle orientation experiences thermal noise. However, the successful outcome strongly depends on the specific problem and the strength of noise.en
dc.description.sponsorshipTU Berlin, Open-Access-Mittel – 2023
dc.identifier.eissn1292-895X
dc.identifier.issn1292-8941
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/20686
dc.identifier.urihttps://doi.org/10.14279/depositonce-19484
dc.language.isoen
dc.publisherSpringer Science and Business Media LLC
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc500 Naturwissenschaften und Mathematik::530 Physik::530 Physik
dc.subject.othersmart active particleen
dc.subject.otherdistance sensingen
dc.subject.otherdirectional sensingen
dc.subject.otherQ learningen
dc.subject.otherreinforcement learningen
dc.titleOptimal navigation of a smart active particle: directional and distance sensing
dc.typeArticle
dc.type.versionpublishedVersion
dcterms.bibliographicCitation.articlenumber48
dcterms.bibliographicCitation.doi10.1140/epje/s10189-023-00309-3
dcterms.bibliographicCitation.issue6
dcterms.bibliographicCitation.journaltitleThe European Physical Journal E
dcterms.bibliographicCitation.originalpublishernameSpringer Nature
dcterms.bibliographicCitation.originalpublisherplaceHeidelberg
dcterms.bibliographicCitation.volume46
dcterms.rightsHolder.referenceCreative-Commons-Lizenz
tub.accessrights.dnbfree
tub.affiliationFak. 2 Mathematik und Naturwissenschaften::Inst. Theoretische Physik::FG Statistische Physik weicher Materie und biologischer Systeme
tub.publisher.universityorinstitutionTechnische Universität Berlin

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