Publication: Tracking Moving Optima Using Kalman-Based Predictions
dc.affiliation.dpto | UC3M. Departamento de Ingeniería de Sistemas y Automática | es |
dc.affiliation.grupoinv | UC3M. Grupo de Investigación: Laboratorio de Robótica (Robotics Lab) | es |
dc.contributor.author | Rossi, Claudio | |
dc.contributor.author | Abderrahim Fichouche, Mohamed | |
dc.contributor.author | Díaz Cabrera, Julio César | |
dc.date.accessioned | 2010-12-20T16:10:34Z | |
dc.date.available | 2010-12-20T16:10:34Z | |
dc.date.issued | 2008-03 | |
dc.description | 30 pages, 23 figures. | |
dc.description.abstract | The dynamic optimization problem concerns finding an optimum in a changing environment. In the field of evolutionary algorithms, this implies dealing with a time-changing fitness landscape. In this paper we compare different techniques for integrating motion information into an evolutionary algorithm, in the case it has to follow a time-changing optimum, under the assumption that the changes follow a nonrandom law. Such a law can be estimated in order to improve the optimum tracking capabilities of the algorithm. In particular, we will focus on first order dynamical laws to track moving objects. A vision-based tracking robotic application is used as testbed for experimental comparison. | |
dc.description.sponsorship | The work of the first and second authors has been carried out under a "Ramón y Cajal" research fellowship from the Ministerio de Ciencia y Tecnología of Spain, and partially funded by projects DPI2005-04302 and DPI2006-03444. | |
dc.description.status | Publicado | |
dc.format.mimetype | application/pdf | |
dc.identifier.bibliographicCitation | Evolutionary Computation, 2008, v. 16, n. 1, p. 1-30 | |
dc.identifier.doi | 10.1162/evco.2008.16.1.1 | |
dc.identifier.issn | 1063-6560 | |
dc.identifier.uri | https://hdl.handle.net/10016/9848 | |
dc.language.iso | eng | |
dc.publisher | MIT Press | |
dc.relation.publisherversion | http://dx.doi.org/10.1162/evco.2008.16.1.1 | |
dc.rights.accessRights | open access | |
dc.subject.eciencia | Robótica e Informática Industrial | |
dc.subject.other | Evolutionary algorithms | |
dc.subject.other | Vision-based tracking | |
dc.subject.other | Dynamic optimization problem | |
dc.subject.other | Time-varying fitness function | |
dc.title | Tracking Moving Optima Using Kalman-Based Predictions | |
dc.type | research article | * |
dc.type.hasVersion | VoR | * |
dspace.entity.type | Publication |
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