Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization

This book focuses on machine learning (ML) assisted evolutionary multi- and many-objective optimization (EMâO). EMâO algorithms, namely EMâOAs, iteratively evolve a set of solutions towards a good Pareto Front approximation. The availability of multiple solution sets over successive generations make...

詳細記述

書誌詳細

主要な著者:	Saxena, Dhish Kumar (著者), Mittal, Sukrit (著者), Deb, Kalyanmoy (著者), Goodman, Erik D. (著者)
団体著者:	SpringerLink (Online service)
フォーマット:	電子媒体 eBook
言語:	英語
出版事項:	Singapore : Springer Nature Singapore : Imprint: Springer, 2024.
版:	1st ed. 2024.
シリーズ:	Genetic and Evolutionary Computation,
主題:	Artificial intelligence. Machine learning. Computational intelligence. Artificial Intelligence. Machine Learning. Computational Intelligence.
オンライン･アクセス:	https://doi.org/10.1007/978-981-99-2096-9
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