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2008

Tracking Moving Optima Using Kalman-Based Predictions

8 years 10 months ago
Tracking Moving Optima Using Kalman-Based Predictions
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. Keywords Evolutionary algorithms, vision-based tracking, dynamic optimization problem, timevarying fitness function.
Claudio Rossi, Mohamed Abderrahim, Julio Cé
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2008
Where EC
Authors Claudio Rossi, Mohamed Abderrahim, Julio César Díaz
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