The contributions in this volume are written by the foremost
international researchers and practitioners in the GP arena. They
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.
Topics include: FINCH: A System for Evolving Java, Practical
Autoconstructive Evolution, The Rubik Cube and GP Temporal Sequence
Learning, Ensemble classifiers: AdaBoost and Orthogonal Evolution
of Teams, Self-modifying Cartesian GP, Abstract Expression Grammar
Symbolic Regression, Age-Fitness Pareto Optimization, Scalable
Symbolic Regression by Continuous Evolution, Symbolic Density
Models, GP Transforms in Linear Regression Situations, Protein
Interactions in a Computational Evolution System, Composition of
Music and Financial Strategies via GP, and Evolutionary Art Using
Summed Multi-Objective Ranks.
Readers will discover large-scale, real-world applications of GP
to a variety of problem domains via in-depth presentations of the
latest and most significant results in GP .
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