Socio-cultural Inspired Metaheuristics

This book presents the latest insights and developments in the field of socio-cultural inspired algorithms. Akin to evolutionary and swarm-based optimization algorithms, socio-cultural algorithms belong to the category of metaheuristics (problem-independent computational methods) and are inspired by...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Kulkarni, Anand J. (Editor), Singh, Pramod Kumar (Editor), Satapathy, Suresh Chandra (Editor), Husseinzadeh Kashan, Ali (Editor), Tai, Kang (Editor)
Format: e-Book
Language:English
Published: Singapore : Springer Nature Singapore : 2019.
Imprint: Springer,
Edition:1st ed. 2019.
Series:Studies in Computational Intelligence, 828
Subjects:
Computational intelligence.
Artificial intelligence.
Mathematical optimization.
Computational Intelligence.
Artificial Intelligence.
Continuous Optimization.
Online Access:Full-text access
Description
Summary:This book presents the latest insights and developments in the field of socio-cultural inspired algorithms. Akin to evolutionary and swarm-based optimization algorithms, socio-cultural algorithms belong to the category of metaheuristics (problem-independent computational methods) and are inspired by natural and social tendencies observed in humans by which they learn from one another through social interactions. This book is an interesting read for engineers, scientists, and students studying/working in the optimization, evolutionary computation, artificial intelligence (AI) and computational intelligence fields.
Physical Description:X, 303 p. 155 illus., 69 illus. in color. online resource.
ISBN:9789811365690
ISSN:1860-9503 ;
DOI:10.1007/978-981-13-6569-0

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