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dc.contributor.authorNasiri Garabolagh, Mahdi
dc.contributor.authorLoran, Edwin
dc.contributor.authorLiebchen, Benno
dc.date.accessioned2023-12-21T16:13:32Z
dc.date.available2023-12-21T16:13:32Z
dc.date.issued2023-12-21
dc.identifier.urihttps://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/4071
dc.descriptionBelow you will find the codes and the trained model weights of the paper "Smart Active Particles Learn and Transcend Bacterial Foraging Strategies".de_DE
dc.rightsCreative Commons Attribution 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectActive Matter Physicsde_DE
dc.subjectTarget Searchde_DE
dc.subjectMachine Learningde_DE
dc.subject.classification310-01 Statistische Physik, Weiche Materie, Biologische Physik, Nichtlineare Dynamikde_DE
dc.subject.ddc530
dc.titleSmart Active Particles Learn and Transcend Bacterial Foraging Strategiesde_DE
dc.typeSoftwarede_DE
tud.unitTUDa


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Creative Commons Attribution 4.0
Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0