Reference chromosome to overcome user fatigue in iec
Inhaltsverzeichnis
Reference
Saez, Y., Isasi, P., Segovia, J., Hernandez, J.C. (2005). Reference chromosome to overcome user fatigue in iec. New Generation Computing, 23(2): 129–142
DOI
http://link.springer.com/article/10.1007%2FBF03037490
Abstract
Evolutionary Computation encompasses computational models that follow a biological evolution metaphor. The success of these techniques is based on the maintenance of the genetic diversity, for which it is necessary to work with large populations. However, it is not always possible to deal with such large populations, for instance, when the adequacy values must be estimated by a human being (Interactive Evolutionary Computation, IEC). This work introduces a new algorithm which is able to perform very well with a very low number of individuals (micropopulations) which speeds up the convergence and it is solving problems with complex evaluation functions. The new algorithm is compared with the canonical genetic algorithm in order to validate its efficiency. Two experimental frameworks have been chosen: table and logotype designs. An objective evaluation measures has been proposed to avoid user interaction in the experiments. In both cases the results show the efficiency of the new algorithm in terms of quality of solutions and convergence speed, two key issues in decreasing user fatigue.
Extended Abstract
Bibtex
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