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001 978-0-387-87623-8
003 DE-He213
005 20251006084427.0
007 cr nn 008mamaa
008 100301s2009 xxu| s |||| 0|eng d
020 _a9780387876238
020 _a99780387876238
024 7 _a10.1007/978-0-387-87623-8
_2doi
100 1 _aWorzel, Bill.
_eeditor.
245 1 0 _aGenetic Programming Theory and Practice VI
_h[electronic resource] /
_cedited by Bill Worzel, Terence Soule, Rick Riolo.
264 1 _aBoston, MA :
_bSpringer US,
_c2009.
300 _bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aGenetic and Evolutionary Computation,
_x1932-0167
520 _aGenetic Programming Theory and Practice VI was developed from the sixth workshop at the University of Michigan's Center for the Study of Complex Systems to facilitate the exchange of ideas and information related to the rapidly advancing field of Genetic Programming (GP). Contributions from the foremost international researchers and practitioners in the GP arena examine the similarities and differences between theoretical and empirical results on real-world problems. The text explores the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application. These contributions address several significant inter-dependent themes which emerged from this year's workshop, including: Making efficient and effective use of test data Sustaining the long term evolvability of our GP systems Exploiting discovered subsolutions for reuse Increasing the role of a Domain Expert In the course of investigating these themes, the chapters describe a variety of techniques in widespread use among practitioners who deal with industrial-scale, real-world problems, such as: Pareto optimization, particularly as a means to limit solution complexity Various types of age-layered populations or niching mechanisms Data partitioning, a priori or adaptively, e.g., via co-evolution Cluster computing or general purpose graphics processors for parallel computing Ensemble/team solutions This work covers applications of GP to a host of domains, including bioinformatics, symbolic regression for system modeling in various settings, circuit design, and financial modeling to support portfolio management. This volume is a unique and indispensable tool for academics, researchers and industry professionals involved in GP, evolutionary computation, machine learning and artificial intelligence.
650 0 _aCOMPUTER SCIENCE.
650 0 _aINFORMATION THEORY.
650 0 _aCOMPUTER SOFTWARE.
650 0 _aELECTRONIC DATA PROCESSING.
650 0 _aARTIFICIAL INTELLIGENCE.
650 1 4 _aCOMPUTER SCIENCE.
650 2 4 _aPROGRAMMING TECHNIQUES.
650 2 4 _aALGORITHM ANALYSIS AND PROBLEM COMPLEXITY.
650 2 4 _aTHEORY OF COMPUTATION.
650 2 4 _aARTIFICIAL INTELLIGENCE (INCL. ROBOTICS).
650 2 4 _aCOMPUTING METHODOLOGIES.
700 1 _aSoule, Terence.
_eeditor.
700 1 _aRiolo, Rick.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780387876221
830 0 _aGenetic and Evolutionary Computation,
_x1932-0167
856 4 0 _uhttp://dx.doi.org/10.1007/978-0-387-87623-8
_zVer el texto completo en las instalaciones del CICY
912 _aZDB-2-SCS
942 _2ddc
_cER
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