000			03816nam a22006375i 4500
001			978-3-662-43631-8
003			DE-He213
005			20200420221254.0
007			cr nn 008mamaa
008			151008s2015 gw | s |||| 0|eng d
020			_a9783662436318 _9978-3-662-43631-8
024	7		_a10.1007/978-3-662-43631-8 _2doi
050		4	_aQA75.5-76.95
072		7	_aUY _2bicssc
072		7	_aUYA _2bicssc
072		7	_aCOM014000 _2bisacsh
072		7	_aCOM031000 _2bisacsh
082	0	4	_a004.0151 _223
100	1		_aBrabazon, Anthony. _eauthor.
245	1	0	_aNatural Computing Algorithms _h[electronic resource] / _cby Anthony Brabazon, Michael O'Neill, Se�an McGarraghy.
250			_a1st ed. 2015.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2015.
300			_aXX, 554 p. 164 illus., 22 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aNatural Computing Series, _x1619-7127
505	0		_aIntroduction -- 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.
520			_aThe 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.
650		0	_aComputer science.
650		0	_aOperations research.
650		0	_aDecision making.
650		0	_aComputers.
650		0	_aArtificial intelligence.
650		0	_aEconomics, Mathematical.
650		0	_aManagement science.
650		0	_aComputational intelligence.
650	1	4	_aComputer Science.
650	2	4	_aTheory of Computation.
650	2	4	_aComputational Intelligence.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aOperations Research, Management Science.
650	2	4	_aOperation Research/Decision Theory.
650	2	4	_aQuantitative Finance.
700	1		_aO'Neill, Michael. _eauthor.
700	1		_aMcGarraghy, Se�an. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783662436301
830		0	_aNatural Computing Series, _x1619-7127
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-662-43631-8
912			_aZDB-2-SCS
942			_cEBK
999			_c52764 _d52764