1.

Record Nr.

UNINA9910734097903321

Autore

Brabazon Anthony

Titolo

Natural Computing Algorithms / / by Anthony Brabazon, Michael O'Neill, Seán McGarraghy

Pubbl/distr/stampa

Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2015

ISBN

3-662-43631-0

Edizione

[1st ed. 2015.]

Descrizione fisica

1 online resource (XX, 554 p. 164 illus., 22 illus. in color.)

Collana

Natural Computing Series, , 2627-6461

Disciplina

006.38

Soggetti

Computer science

Computational intelligence

Artificial intelligence

Operations research

Management science

Social sciences—Mathematics

Theory of Computation

Computational Intelligence

Artificial Intelligence

Operations Research, Management Science

Operations Research and Decision Theory

Mathematics in Business, Economics and Finance

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Bibliographic Level Mode of Issuance: Monograph

Nota di contenuto

Introduction -- Introduction to Evolutionary Computing -- Genetic Algorithms -- Extending the Genetic Algorithm -- Evolution Strategies and Evolutionary Programming -- Differential Evolution -- Genetic Programming -- Particle Swarm Algorithms -- Ant Algorithms -- Honeybee Algorithms -- Other Social Algorithms -- Bacterial Foraging Algorithms -- Neural Networks for Supervised Learning -- Neural Networks for Unsupervised Learning -- Neuroevolution -- Artificial Immune Systems -- An Introduction to Developmental and Grammatical Computing -- Grammar-Based and Developmental Genetic Programming -- Grammatical Evolution -- TAG3P and



Developmental TAG3P -- Genetic Regulatory Networks -- An Introduction to Physics-Inspired Computing -- Physics-Inspired Computing Algorithms -- Quantum-Inspired Evolutionary Algorithms -- Plant-Inspired Algorithms -- Chemistry-Inspired Algorithms -- Conclusions -- References -- Index.

Sommario/riassunto

The field of natural computing has been the focus of a substantial research effort in recent decades. One particular strand of this research concerns the development of computational algorithms using metaphorical inspiration from systems and phenomena that occur in the natural world. These naturally inspired computing algorithms have proven to be successful problem-solvers across domains as diverse as management science, bioinformatics, finance, marketing, engineering, architecture and design. This book is a comprehensive introduction to natural computing algorithms, suitable for academic and industrial researchers and for undergraduate and graduate courses on natural computing in computer science, engineering and management science.