000 | 03188nam a22005535i 4500 | ||
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001 | 978-3-642-17310-3 | ||
003 | DE-He213 | ||
005 | 20140220083750.0 | ||
007 | cr nn 008mamaa | ||
008 | 110915s2011 gw | s |||| 0|eng d | ||
020 |
_a9783642173103 _9978-3-642-17310-3 |
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024 | 7 |
_a10.1007/978-3-642-17310-3 _2doi |
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050 | 4 | _aQA75.5-76.95 | |
072 | 7 |
_aUY _2bicssc |
|
072 | 7 |
_aUYA _2bicssc |
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072 | 7 |
_aCOM014000 _2bisacsh |
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072 | 7 |
_aCOM031000 _2bisacsh |
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082 | 0 | 4 |
_a004.0151 _223 |
100 | 1 |
_aMiller, Julian F. _eeditor. |
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245 | 1 | 0 |
_aCartesian Genetic Programming _h[electronic resource] / _cedited by Julian F. Miller. |
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2011. |
|
300 |
_aXXII, 346 p. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aNatural Computing Series, _x1619-7127 |
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505 | 0 | _aIntroduction -- Cartesian Genetic Programming -- Modular Cartesian Genetic Programming -- Self-modifying Cartesian Genetic Programming -- Evolution of Electronic Circuits -- Image Processing -- Developmental Approaches -- Artificial Neural Approaches -- Medical Applications -- Hardware Acceleration -- Control Applications -- Evolutionary Art -- Future Directions -- App. A, A Bibliography of CGP Papers -- App. B, CGP Software. | |
520 | _aCartesian Genetic Programming (CGP) is a highly effective and increasingly popular form of genetic programming. It represents programs in the form of directed graphs, and a particular characteristic is that it has a highly redundant genotype–phenotype mapping, in that genes can be noncoding. It has spawned a number of new forms, each improving on the efficiency, among them modular, or embedded, CGP, and self-modifying CGP. It has been applied to many problems in both computer science and applied sciences. This book contains chapters written by the leading figures in the development and application of CGP, and it will be essential reading for researchers in genetic programming and for engineers and scientists solving applications using these techniques. It will also be useful for advanced undergraduates and postgraduates seeking to understand and utilize a highly efficient form of genetic programming. | ||
650 | 0 | _aComputer science. | |
650 | 0 | _aInformation theory. | |
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aInformation systems. | |
650 | 0 | _aComputer aided design. | |
650 | 0 | _aComputer engineering. | |
650 | 1 | 4 | _aComputer Science. |
650 | 2 | 4 | _aTheory of Computation. |
650 | 2 | 4 | _aElectrical Engineering. |
650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
650 | 2 | 4 | _aComputer-Aided Engineering (CAD, CAE) and Design. |
650 | 2 | 4 | _aComputer Appl. in Arts and Humanities. |
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783642173097 |
830 | 0 |
_aNatural Computing Series, _x1619-7127 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-642-17310-3 |
912 | _aZDB-2-SCS | ||
999 |
_c107235 _d107235 |