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Tracking moving optima using Kalman-based predictions
Rossi, Claudio and Abderrahim, Mohamed and Diaz, Julio Cesar
Tracking moving optima using Kalman-based predictions.
"Evolutionary Computation", v. 16
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.
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