• FINCH: A System for Evolving Java (Bytecode).- Towards Practical Autoconstructive Evolution: Self-Evolution of Problem-Solving Genetic Programming Systems.- The Rubik Cube and GP Temporal Sequence Learning: An Initial Study.- Ensemble Classifiers: AdaBoost and Orthogonal Evolution of Teams.- Covariant Tarpeian Method for Bloat Control in Genetic Programming.- A Survey of Self Modifying Cartesian Genetic Programming.- Abstract Expression Grammar Symbolic Regression.- Age-Fitness Pareto Optimization.- Scalable Symbolic Regression by Continuous Evolution with Very Small Populations.- Symbolic Density Models of One-in-a-Billion Statistical Tails via Importance Sampling and Genetic Programming.- Genetic Programming Transforms in Linear Regression Situations.- Exploiting Expert Knowledge of Protein-Protein Interactions in a Computational Evolution System for Detecting Epistasis.- Composition of Music and Financial Strategies via Genetic Programming.- Evolutionary Art Using Summed Multi-Objective Ranks.

From the reviews: "The book consists of 14 papers and an introduction. The applications it considers clearly demonstrate the maturity of GP techniques, and their ability to efficiently address difficult problem instances. ... A specialized audience of experts in genetic algorithms will find state-of-the-art applications and methodologies in this book. It will also be of interest to practitioners for the large number of applications discussed, and to advanced students and researchers for the numerous opportunities for investigation and thesis topics." (Renato De Leone, ACM Computing Reviews, July, 2011)