| 书目名称 | Optinformatics in Evolutionary Learning and Optimization | | 编辑 | Liang Feng,Yaqing Hou,Zexuan Zhu | | 视频video | | | 概述 | Summarizes recent algorithmic advances toward realizing the notion of optinformatics in evolutionary learning and optimization.Contains a variety of practical applications, including inter-domain lear | | 丛书名称 | Adaptation, Learning, and Optimization | | 图书封面 |  | | 描述 | .This book provides readers the recent algorithmic advances towards realizing the notion of .optinformatics. in evolutionary learning and optimization. The book also provides readers a variety of practical applications, including inter-domain learning in vehicle route planning, data-driven techniques for feature engineering in automated machine learning, as well as evolutionary transfer reinforcement learning. Through reading this book, the readers will understand the concept of .optinformatics., recent research progresses in this direction, as well as particular algorithm designs and application of .optinformatics...Evolutionary algorithms (EAs) are adaptive search approaches that take inspiration from the principles of natural selection and genetics. Due to their efficacy of global search and ease of usage, EAs have been widely deployed to address complex optimization problems occurring in a plethora of real-world domains, including image processing, automation of machine learning, neural architecture search, urban logistics planning, etc. Despite the success enjoyed by EAs, it is worth noting that most existing EA optimizers conduct the evolutionary search process from scratch, | | 出版日期 | Book 2021 | | 关键词 | Optinformatics; Knowledge Reuse; Evolutionary Computation; Memetic Computation; Meta-heuristics; Transfer | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-70920-4 | | isbn_softcover | 978-3-030-70922-8 | | isbn_ebook | 978-3-030-70920-4Series ISSN 1867-4534 Series E-ISSN 1867-4542 | | issn_series | 1867-4534 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 18:40:51
