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MARC Record from marc_columbia

Record ID marc_columbia/Columbia-extract-20221130-009.mrc:274234189:6407
Source marc_columbia
Download Link /show-records/marc_columbia/Columbia-extract-20221130-009.mrc:274234189:6407?format=raw

LEADER: 06407cam a2200913Ma 4500
001 4246510
005 20221111173347.0
006 m o d
007 cr cn|||||||||
008 950623s1996 maua ob 001 0 eng d
010 $z 95024489
035 $a(OCoLC)ocm42854439
035 $a(NNC)4246510
040 $aN$T$beng$epn$cN$T$dOCL$dOCLCQ$dMUQ$dOCLCQ$dDST$dYDXCP$dOCLCQ$dTPH$dOCLCQ$dN$T$dSBM$dTUU$dOCLCQ$dTNF$dNEG$dOCLCQ$dZCU$dOCLCF$dOCLCA$dOCLCQ$dCOO$dSLY$dOCLCQ$dNLGGC$dOCLCQ$dD6H$dOCLCQ$dSUR$dOCLCQ$dRRP$dOCLCA$dU3W$dOCLCA$dMNS$dLUE$dOCLCO$dHCC$dOCLCO$dUUM$dINARC$dCEF$dXOS$dXQH$dMUO$dOCLCQ$dTOF$dWYU$dMITPR$dCANPU$dYOU$dGDC$dOCLCO$dBRX$dAU@$dOCLCO$dCNTRU$dOCLCO$dXMC$dOCLCQ$dRDF$dVDB$dOCLCA$dLUN$dAJS$dTUHNV$dOCLCO
019 $a880192644$a961671504$a962577184$a984870524$a1020519005$a1035694747$a1044033328$a1055841324$a1056289135$a1078043618$a1097295031$a1105734947$a1123787822$a1125384209$a1127918699$a1136180386$a1167514669$a1188966520$a1196916036$a1243573755
020 $a9780262280013$q(electronic bk.)
020 $a0262280019$q(electronic bk.)
020 $a0585030944$q(electronic bk.)
020 $a9780585030944$q(electronic bk.)
020 $a9780262133166$q(alk. paper)
020 $a0262133164$q(alk. paper)
020 $a9780262631853$q(paperback)
020 $a0262631857$q(paperback)
035 $a(OCoLC)42854439$z(OCoLC)880192644$z(OCoLC)961671504$z(OCoLC)962577184$z(OCoLC)984870524$z(OCoLC)1020519005$z(OCoLC)1035694747$z(OCoLC)1044033328$z(OCoLC)1055841324$z(OCoLC)1056289135$z(OCoLC)1078043618$z(OCoLC)1097295031$z(OCoLC)1105734947$z(OCoLC)1123787822$z(OCoLC)1125384209$z(OCoLC)1127918699$z(OCoLC)1136180386$z(OCoLC)1167514669$z(OCoLC)1188966520$z(OCoLC)1196916036$z(OCoLC)1243573755
037 $a3927$bMIT Press
037 $a9780262280013$bMIT Press
050 4 $aQH441.2$b.M55 1996eb
072 0 $aX300
072 7 $aSCI$x029000$2bisacsh
082 04 $a575.1/01/13$220
084 $aO242. 1$2clc
084 $aQ3$2clc
049 $aZCUA
100 1 $aMitchell, Melanie$c(Computer scientist)
245 13 $aAn introduction to genetic algorithms /$cMelanie Mitchell.
260 $aCambridge, Mass. :$bMIT Press,$c©1996.
264 4 $c©1996
300 $a1 online resource (viii, 205 pages) :$billustrations
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
347 $atext file$bPDF$2rda
490 1 $aComplex adaptive systems
500 $a"A Bradford book."
504 $aIncludes bibliographical references (pages 191-201) and index.
505 0 $a1. Genetic Algorithms: An Overview -- 2. Genetic Algorithms in Problem Solving -- 3. Genetic Algorithms in Scientific Models -- 4. Theoretical Foundations of Genetic Algorithms -- 5. Implementing a Genetic Algorithm -- 6. Conclusions and Future Directions.
588 0 $aPrint version record.
520 $aGenetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics--particularly in machine learning, scientific modeling, and artificial life--and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.
650 0 $aGenetic algorithms.
650 0 $aGenetics$xComputer simulation.
650 0 $aGenetics$xMathematical models.
650 12 $aModels, Genetic
650 22 $aAlgorithms
650 22 $aComputer Simulation
650 6 $aGénétique$xSimulation par ordinateur.
650 6 $aGénétique$xModèles mathématiques.
650 7 $aSCIENCE$xLife Sciences$xGenetics & Genomics.$2bisacsh
650 07 $aGenetics$xComputer simulation.$2cct
650 07 $aGenetics$xMathematical models.$2cct
650 07 $aModels, Genetic.$2cct
650 07 $aComputer simulation.$2cct
650 07 $aAlgorithms.$2cct
650 7 $aGenetic algorithms.$2fast$0(OCoLC)fst00939996
650 7 $aGenetics$xComputer simulation.$2fast$0(OCoLC)fst00940119
650 7 $aGenetics$xMathematical models.$2fast$0(OCoLC)fst00940127
650 17 $aAlgoritmen.$2gtt$0(NL-LeOCL)078429358
650 17 $aEvolutie.$2gtt$0(NL-LeOCL)078501733
650 17 $aGenetica.$2gtt$0(NL-LeOCL)078516900
650 7 $aGenetics.$2hilcc
650 7 $aBiology.$2hilcc
650 7 $aHealth & Biological Sciences.$2hilcc
653 0 $aGenetics$aMathematical models
653 $aCOMPUTER SCIENCE/General
655 4 $aElectronic books.
655 0 $aElectronic books.
776 08 $iPrint version:$aMitchell, Melanie, Professor.$tIntroduction to genetic algorithms.$dCambridge, Mass. : MIT Press, ©1996$z0262133164$w(DLC) 95024489$w(OCoLC)32822438
830 0 $aComplex adaptive systems.
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio4246510$zAll EBSCO eBooks
852 8 $blweb$hEBOOKS