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Niching in evolution strategies and its application to laser pulse shaping
EA'05 Proceedings of the 7th international conference on Artificial Evolution
Gaining Insights into Laser Pulse Shaping by Evolution Strategies
IWINAC '07 Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks
Evolving robust controller parameters using covariance matrix adaptation
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IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
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This paper presents a new parameterization method for the Evolution Strategies (ES) field, and its application to a challenging real-life high-dimensional Physics optimization problem, namely Femtosecond Laser Pulse Shaping. The so-called Complete-Basis-Functions Parameterization method (CBFP), to be introduced here for the first time, is developed for tackling efficiently the given laser optimization task, but nevertheless is a general method that can be used for learning any n-variables functions. The emphasis is on dimensionality reduction of the search space and the speeding-up of the convergence process respectively. This is achieved by learning the target function by using complete-basis functions as building blocks in an evolutionary search. The method is shown to boost the learning process of the given laser problem, and to yield highly satisfying results.