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The complete-basis-functions parameterization in ES and its application to laser pulse shaping

机译：ES中的完整基础函数参数化及其应用于激光脉冲整形

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摘要

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.
机译：本文提出了一个新的参数化方法，用于演进策略，其在具有挑战性的现实生活高维物理优化问题上，即飞秒激光脉冲整形。所谓的完整基本函数参数化方法（CBFP），首次介绍，用于有效地解决给定的激光优化任务，但最终是可以的一般方法用于学习任何 n - variables函数。重点是分别对搜索空间的维度降低和收敛过程的加速。这是通过在进化搜索中使用完整的基础函数来学习目标功能来实现的。该方法被示出促进给定激光问题的学习过程，并产生高度满足的结果。

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