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001			978-0-387-87623-8
003			DE-He213
005			20160302164221.0
007			cr nn 008mamaa
008			100301s2009 xxu| s |||| 0|eng d
020			_a9780387876238 _9978-0-387-87623-8
024	7		_a10.1007/978-0-387-87623-8 _2doi
050		4	_aQA76.6-76.66
072		7	_aUM _2bicssc
072		7	_aCOM051000 _2bisacsh
082	0	4	_a005.11 _223
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			_aXIV, 274 p. 100 illus. _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
505	0		_aGenetic Programming: Theory and Practice -- APopulationBased Study ofEvolutionaryDynamics inGeneticProgramming -- An Application of Information Theoretic Selection to Evolution of Models with Continuous-valued Inputs -- Pareto Cooperative-Competitive Genetic Programming: A Classification Benchmarking Study -- Genetic Programming with Historically Assessed Hardness -- Crossover and Sampling Biases on Nearly Uniform Landscapes -- Analysis of theEffects ofElitismonBloat inLinear and Tree-basedGenetic Programming -- Automated Extraction of Expert Domain Knowledge from Genetic Programming Synthesis Results -- Does Complexity Matter? Artificial Evolution, Computational Evolution and the Genetic Analysis of Epistasis in Common Human Diseases. -- Exploiting Trustable Models via Pareto GP for Targeted Data Collection -- Evolving Effective Incremental Solvers for SAT with a Hyper-Heuristic Framework Based on Genetic Programming -- ConstrainedGenetic Programming toMinimizeOverfitting in StockSelection -- Co-Evolving Trading Strategies toAnalyzeBoundedRationality inDouble Auction Markets. -- Profiling Symbolic Regression-Classification -- Accelerating Genetic Programming through Graphics Processing Units. -- Genetic Programming for Incentive-Based Design within a Cultural Algorithms Framework.
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	_aComputer programming.
650		0	_aComputers.
650		0	_aAlgorithms.
650		0	_aArtificial intelligence.
650	1	4	_aComputer Science.
650	2	4	_aProgramming Techniques.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aComputing Methodologies.
650	2	4	_aTheory of Computation.
650	2	4	_aAlgorithm Analysis and Problem Complexity.
700	1		_aWorzel, Bill. _eeditor.
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
912			_aZDB-2-SCS
999			_c183953 _d183953