RT Journal Article
T1 Tracking Moving Optima Using Kalman-Based Predictions
A1 Rossi, Claudio
A1 Abderrahim Fichouche, Mohamed
A1 Díaz Cabrera, Julio César
AB 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.
PB MIT Press
SN 1063-6560
YR 2008
FD 2008-03
LK https://hdl.handle.net/10016/9848
UL https://hdl.handle.net/10016/9848
LA eng
NO 30 pages, 23 figures.
NO 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 partiallyfunded by projects DPI2005-04302 and DPI2006-03444.
DS e-Archivo
RD 24 may. 2024