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dc.contributor.author
de Paula, Mariano
dc.contributor.author
Acosta, Gerardo Gabriel
dc.contributor.author
Martinez, Ernesto Carlos
dc.date.available
2017-08-15T16:49:33Z
dc.date.issued
2014-10
dc.identifier.citation
de Paula, Mariano; Acosta, Gerardo Gabriel; Martinez, Ernesto Carlos; On-line policy learning and adaptation for real-time personalization of an artificial pancreas; Elsevier; Expert Systems with Applications; 42; 4; 10-2014; 2234-2255
dc.identifier.issn
0957-4174
dc.identifier.uri
http://hdl.handle.net/11336/22463
dc.description.abstract
The dynamic complexity of the glucose-insulin metabolism in diabetic patients is the main obstacle towards widespread use of an artificial pancreas. The significant level of subject-specific glycemic variability requires continuously adapting the control policy to successfully face daily changes in patient´s metabolism and lifestyle. In this paper, an on-line selective reinforcement learning algorithm that enables real-time adaptation of a control policy based on ongoing interactions with the patient so as to tailor the artificial pancreas is proposed. Adaptation includes two online procedures: on-line sparsification and parameter updating of the Gaussian process used to approximate the control policy. With the proposed sparsification method, the support data dictionary for on-line learning is modified by checking if in the arriving data stream there exists novel information to be added to the dictionary in order to personalize the policy. Results obtained in silico experiments demonstrate that on-line policy learning is both safe and efficient for maintaining blood glucose variability within the normoglycemic range.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.subject
Diabetes
dc.subject
Gaussian Processes
dc.subject
Glycemic Variability
dc.subject
On-Line Sparsification
dc.subject
Policy Learning
dc.subject
Reinforcement Learning
dc.subject.classification
Ingeniería de Sistemas y Comunicaciones
dc.subject.classification
Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
dc.title
On-line policy learning and adaptation for real-time personalization of an artificial pancreas
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2017-08-04T15:35:26Z
dc.journal.volume
42
dc.journal.number
4
dc.journal.pagination
2234-2255
dc.journal.pais
Países Bajos
dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: de Paula, Mariano. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ingeniería Olavarria. Departamento de Electromecánica. Grupo INTELYMEC; Argentina. Universidad Nacional del Centro de la Pcia.de Bs.as.. Centro de Investigaciones En Fisica E Ingenieria del Centro de la Provincia de Buenos Aires. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Tandil. Centro de Investigaciones En Fisica E Ingenieria del Centro de la Provincia de Buenos Aires. - Provincia de Buenos Aires. Gobernacion. Comision de Invest.cientificas. Centro de Investigaciones En Fisica E Ingenieria del Centro de la Provincia de Buenos Aires; Argentina
dc.description.fil
Fil: Acosta, Gerardo Gabriel. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ingenieria Olavarria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: Martinez, Ernesto Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
dc.journal.title
Expert Systems with Applications
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.eswa.2014.10.038
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0957417414006629
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