Interactive Evolutionary Computing (EASY-IEC) MATLAB Toolbox

Implementation of Interactive Evolutionary Computation (IEC)
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Mise à jour 11 juil. 2014

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In some real-life optimization problems the objectives are often non-commensurable and are explicitly/mathematically not available.
Interactive Evolutionary Computation (IEC) can effectively handle these problems.
IEC uses human evaluation in the optimization system. Simply stated, IEC is a technique from the class of evolutionary algorithms (EAs), whose fitness function is replaced by a human. As in interactive evolution, the user selects one or more individual(s) which survive(s) and reproduce(s) (with variation) to constitute a new generation, IEC uses two different spaces for its search. Thehuman user evaluates the output of the target system according to the distance between the target goal and the system output in psychological space. On the other hand, the EA searches in the parameter space. It can be said that the IEC is the optimization technology where the EA and a human search are cooperatively based on the mapping between these two spaces.

More information, html help and three papers about the application of this toolbox are also available from here:
http://www.abonyilab.com/software-and-data/easy_iec

Citation pour cette source

Janos Abonyi (2026). Interactive Evolutionary Computing (EASY-IEC) MATLAB Toolbox (https://fr.mathworks.com/matlabcentral/fileexchange/47206-interactive-evolutionary-computing-easy-iec-matlab-toolbox), MATLAB Central File Exchange. Extrait(e) le .

Compatibilité avec les versions de MATLAB
Créé avec R14SP1
Compatible avec toutes les versions
Plateformes compatibles
Windows macOS Linux
Version Publié le Notes de version
1.0.0.0