An alternative measurement of the entropy evolution of a genetic algorithm
Entidad
UAM. Departamento de Ingeniería InformáticaEditor
The European Multidisciplinary Society for Modelling and Simulation Technology (EUROSIS)Fecha de edición
2009Cita
Modelling and simulation 2009 : the European Simulation and Modelling Conference 2009, ESM '2009. Ghent: EUROSIS, 2009ISBN
9789077381526Financiado por
This work has been partially sponsored by MICINN, project TIN2008-02081/TIN and by DGUI CAM/UAM, project CCG08-UAM/TIC-4425.Materias
Genetic Algorithms; Entropy; Thermodynamics; Kolmogorov Complexity; InformáticaNota
This is an electronic version of the paper presented at The European Simulation and Modelling Conference (ESM), held in Leicester (United Kingdom) on 2009Derechos
© EUROSIS-ETI 2009Resumen
In a genetic algorithm, fluctuations of the entropy of a
genome over time are interpreted as fluctuations of the
information that the genome’s organism is storing
about its environment, being this reflected in more
complex organisms. The computation of this entropy
presents technical problems due to the small population
sizes used in practice. In this work we propose and test
an alternative way of measuring the entropy variation
in a population by means of algorithmic information
theory, where the entropy variation between two
generational steps is the Kolmogorov complexity of the
first step conditioned to the second one. We also report
experimental differences in entropy evolution between
systems in which sexual reproduction is present or
absent.
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Google Scholar:Cebrián Ramos, Manuel
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Alfonseca, Manuel
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Ortega de la Puente, Alfonso
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