TY  - BOOK
AU  - Brabazon,Anthony
AU  - O'Neill,Michael
AU  - McGarraghy,Seán
ED  - SpringerLink (Online service)
TI  - Natural Computing Algorithms
T2  - Natural Computing Series,
SN  - 9783662436318
AV  - QA75.5-76.95 
U1  - 004.0151 23
PY  - 2015///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg, Imprint: Springer
KW  - Computer Science
KW  - Operations research
KW  - Decision making
KW  - computers
KW  - Artificial intelligence
KW  - Economics, Mathematical
KW  - Management science
KW  - Computational Intelligence
KW  - Theory of Computation
KW  - Artificial Intelligence (incl. Robotics)
KW  - Operations Research, Management Science
KW  - Operation Research/Decision Theory
KW  - Quantitative Finance
N1  - 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
N2  - 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
UR  - http://dx.doi.org/10.1007/978-3-662-43631-8
ER  -