An advanced evolution should not repeat its past errors - Archive ouverte HAL
Communication Dans Un Congrès Année : 1996

An advanced evolution should not repeat its past errors

Résumé

A safe control of genetic evolution consists in preventing past errors of evolution from be­ing repeated. This could be done by keeping track of the history of evolution, but main­taining and exploiting the complete history is intractable. This paper investigates the use of machine learning (ML), in order to extract manageable information from this history. More pre­cisely, induction from examples of past trials and errors provides rules discriminating er­rors from successful trials. Such rules allow to a priori estimate the desirability of future trials; this knowledge can support powerful control strategies. SeveraI strategies of ML-based control are ap­plied to a genetic algorithm, and tested on the RoyaI Road, a GA-deceptive, and a com­binatorial optimization problem. Comparing mutation control with crossover control yields unexpected results.
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hal-00116421 , version 1 (31-08-2021)

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  • HAL Id : hal-00116421 , version 1

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Caroline Ravisé, Michèle Sebag. An advanced evolution should not repeat its past errors. 13th International Conference on Machine Learning (ICML96), 1996, Strasbourg, France. pp.400-408. ⟨hal-00116421⟩
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