Can I read Optinformatics in Evolutionary Learning and Optimization (Adaptation, Learning, and Optimization, 25) on EtoBox?

Optinformatics in Evolutionary Learning and Optimization (Adaptation, Learning, and Optimization, 25) by Liang Feng,Yaqing Hou,Zexuan Zhu (auth.) is a nonfiction available to read on EtoBox.

What is Optinformatics in Evolutionary Learning and Optimization (Adaptation, Learning, and Optimization, 25) about?

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 scra

Who reads Optinformatics in Evolutionary Learning and Optimization (Adaptation, Learning, and Optimization, 25)?

Author

Liang Feng,Yaqing Hou,Zexuan Zhu (auth.)

Publisher

Springer International Publishing AG

Published

2021

Language

EN

ISBN

9783030709204

Category

nonfiction

Subjects

Computer Science, Engineering, Science