Tracking moving optima using Kalman-based predictions

Rossi, Claudio and Abderrahim, Mohamed and Diaz, Julio Cesar (2008). Tracking moving optima using Kalman-based predictions. "Evolutionary Computation", v. 16 (n. 1); pp. 1-30. ISSN 1063-6560.

Description

Title: Tracking moving optima using Kalman-based predictions
Author/s:
  • Rossi, Claudio
  • Abderrahim, Mohamed
  • Diaz, Julio Cesar
Item Type: Article
Título de Revista/Publicación: Evolutionary Computation
Date: March 2008
ISSN: 1063-6560
Volume: 16
Subjects:
Freetext Keywords: Evolutionary algorithms, vision-based tracking, dynamic optimization problem, timevarying fitness function.
Faculty: E.T.S.I. Industriales (UPM)
Department: Automática, Ingeniería Electrónica e Informática Industrial [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

The dynamic optimization problem concerns finding an optimum in a changing environment. In the field of evolutionary algorithms, this implies dealing with a timechanging 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.

More information

Item ID: 2840
DC Identifier: http://oa.upm.es/2840/
OAI Identifier: oai:oa.upm.es:2840
Official URL: http://www.mitpressjournals.org/toc/evco/16/1
Deposited by: Memoria Investigacion
Deposited on: 16 Apr 2010 11:58
Last Modified: 20 Apr 2016 12:29
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