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(9)   

• Dynamics of evolutionary robustness
  Alan Piszcz and Terence Soule GECCO 2006: Proceedings of the 8th annual conference on Genetic and evolutionary computation, 1, page871--878. Seattle, Washington, USA, ACM Press, 8-12 July2006.
  to robustness, programming, elitism, genetic theory algorithms, dynamics, by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• Genetic Programming Theory and Practice
  Bill Worzel and Rick L. Riolo Genetic Programming Theory and Practise, chapter 1, Kluwer, (2003)
  to biology, programming, genetic genes bloat, algorithms, diversity, theoretical dynamics, population particulate by brazovayeye and 1 other person on Jun 19, 2008, 5:35 PM
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• Dynamical model reconstruction and accurate prediction of power-pool time series
  Vinay Varadan and Henry Leung and Eloi Bosse IEEE Transactions on Instrumentation and Measurement55(1):327--336February2006.
  to series, predictor, correlation-dimension basis demand, Chaos, Lyapunov least neural Lyapunov-spectrum, function methods, time low-dimensional squares dimension, power Lyapunov-dimension (RBF) embedding attractor-dimension, GP, demand analysis, dynamical system, and prediction, price price, nonlinearity power-pool estimates, delay systems, dynamics, chaos, fractal-dimension series model embedding, approximations, net state-space radial fractals, programming, algorithms, theory, time-series markets, calculation, prediction chaotic network, stationarity exponents, genetic tests, local fractal reconstruction, estimation, nonlinear by brazovayeye on Jun 19, 2008, 5:35 PM
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• Approximation of Chaotic Dynamics by Using Smaller Number of Data Based upon the Genetic Programming and Its Applications
  Yoshikazu Ikeda and Shozo Tokinaga IEICE Transactions on fundamentals of electronics, communications and computer sciencesE83A(8):1599--1607(2000)
  to Processing, system programming, Nonlinear economics,identification,prediction Signal genetic identification, chaotic algorithms, dynamics, nonlinear by brazovayeye on Jun 19, 2008, 5:35 PM
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• Evolution of Mesh Refinement Rules for Impact Dynamics
  Daniel Howard and Simon C. Roberts Proceedings of the 2000 Congress on Evolutionary Computation CEC00, page1297--1303. La Jolla Marriott Hotel La Jolla, California, USA, IEEE Press, 6-9 July2000.
  to evolution, computing, equations, i,mpact refinement engineering densities, ball, impact learning, metal differential rule evolutionary mechanical applications algorithms, mesh computation, Programming, impact, speed adaptive (mechanical), plate (artificial learning partial spherical material intelligence), cells, refinement, genetic high dynamics, novel by brazovayeye on Jun 19, 2008, 5:35 PM
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• Nonlinear model structure identification using genetic programming
  Gary J. Gray and David J. Murray-Smith and Yun Li and Ken C. Sharman and Thomas Weinbrenner Control Engineering Practice6(11):1341--1352(1998)
  to equations, Nonlinear control, analysis systems), Water Helicopter Control Differential programming, rotors, tanks, simulation, (control algorithms, helicopter control analysis, Computer Identification Error Mathematical system Speed genetic identification, systems, dynamics, models, nonlinear by brazovayeye on Jun 19, 2008, 5:35 PM
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• The MIT Beer Distribution Game Revisited: Genetic Machine Learning and Managerial Behavior in a Dynamic Decision Making Experiment
  Andreas Geyer-Schulz Genetic Algorithms and Soft Computing, volume8ofStudies in Fuzziness and Soft Computing, page658--682. Heidelberg, Physica-Verlag, September1996.
  to gaming, learning, organizational programming. system programming, fuzzy genetic Experimental simulation, economics, algorithms, dynamics, by brazovayeye on Jun 19, 2008, 5:35 PM
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• Towards identifying populations that increase the likelihood of success in genetic programming
  Jason M. Daida GECCO 2005: Proceedings of the 2005 conference on Genetic and evolutionary computation, 2, page1627--1634. Washington DC, USA, ACM Press, 25-29 June2005.
  to building experimentation, theory problem selection methods, populations, programming programming, difficulty, genetic initial binomial-3, performance, algorithms, blocks, dynamics, population by brazovayeye and 1 other person on Jun 19, 2008, 5:35 PM
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• Unbounded evolutionary dynamics in a system of agents that actively process and transform their environment
  Alastair Channon Genetic Programming and Evolvable Machines7(3):253--281October2006.
  to genomes, Coevolution, Evolutionary Variable-size selection, life, Biotic artificial Emergence dynamics, by brazovayeye and 1 other person on Jun 19, 2008, 5:35 PM
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