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001412368 020__ $$a9780262290791$$q(electronic bk.)
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001412368 035__ $$a(OCoLC)827304142
001412368 035__ $$a(OCoLC-P)827304142
001412368 040__ $$aOCoLC-P$$beng$$epn$$cOCoLC-P
001412368 050_4 $$aQA76.623$$b.A38 1996
001412368 08204 $$a006.3$$222
001412368 24500 $$aAdvances in genetic programming.$$nVol. 2 /$$cedited by Peter J. Angeline and Kenneth E. Kinnear, Jr.
001412368 260__ $$aCambridge, Mass. ;$$aLondon :$$bMIT Press,$$c©1996.
001412368 300__ $$a1 online resource (xi, 538 pages) :$$billustrations.
001412368 336__ $$atext$$btxt$$2rdacontent
001412368 337__ $$acomputer$$bc$$2rdamedia
001412368 338__ $$aonline resource$$bcr$$2rdacarrier
001412368 4901_ $$aComplex adaptive systems
001412368 4900_ $$aA Bradford book
001412368 506__ $$aAccess limited to authorized users.
001412368 520__ $$aGenetic programming, a form of genetic algorithm that evolves programs and program-like executable structures, is a new paradigm for developing reliable, time- and cost-effective applications. The second volume of Advances in Genetic Programming highlights many of the most recent technical advances in this increasingly popular field.Genetic programming, a form of genetic algorithm that evolves programs and program-like executable structures, is a new paradigm for developing reliable, time- and cost-effective applications. The second volume of Advances in Genetic Programming highlights many of the most recent technical advances in this increasingly popular field. The twenty-three contributions are divided into four parts: Variations on the Genetic Programming Theme; Hierarchical, Recursive, and Pruning Genetic Programs; Analysis and Implementation Issues; and New Environments for Genetic Programming. The first part extends the core concepts of genetic programming through the addition of new evolutionary techniques--adaptive and self-adaptive crossover methods, hill climbing operators, and the inclusion of introns into the representation. Creating more concise executable structures is a long-term research topic in genetic programming. The second part describes the field's most recent efforts, including the dynamic manipulation of automatically defined functions, evolving logic programs that generate recursive structures, and using minimum description length heuristics to determine when and how to prune evolving structures. The third part takes up the many implementation and analysis issues associated with evolving programs. Advanced applications of genetic programming to nontrivial real-world problems are described in the final part: remote sensing of pressure ridges in Arctic sea ice formations from satellite imagery, economic prediction through model evolution, the evolutionary development of stress and loading models for novel materials, and data mining of a large customer database to optimize responses to special offers.
001412368 588__ $$aOCLC-licensed vendor bibliographic record.
001412368 650_0 $$aGenetic programming (Computer science)
001412368 650_0 $$aComputer programming.
001412368 653__ $$aCOMPUTER SCIENCE/Artificial Intelligence
001412368 653__ $$aCOMPUTER SCIENCE/Machine Learning & Neural Networks
001412368 655_0 $$aElectronic books
001412368 7001_ $$aKinnear, Kenneth E.
001412368 7001_ $$aAngeline, Peter J.
001412368 852__ $$bebk
001412368 85640 $$3MIT Press$$uhttps://univsouthin.idm.oclc.org/login?url=https://doi.org/10.7551/mitpress/1109.001.0001?locatt=mode:legacy$$zOnline Access through The MIT Press Direct
001412368 85642 $$3OCLC metadata license agreement$$uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
001412368 909CO $$ooai:library.usi.edu:1412368$$pGLOBAL_SET
001412368 980__ $$aBIB
001412368 980__ $$aEBOOK
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001412368 983__ $$aOnline