1 Genetic Programming: Theory and Practice.- 2 An Essay Concerning Human Understanding for Genetic Programming.- 3 Classification of Gene Expression Data with Genetic Programming.- 4 Artificial Regulatory Networks and Genetic Programming.- 5 Using Software Engineering Knowledge to Drive Genetic Program Design Using Cultural Algorithms.- 6 Continuous Hierarchical Fair Competition Model for Sustainable Innovation in Genetic Programming.- 7 What Makes a Problem GP-Hard?.- 8 A Probalistic Model of Size Drift.- 9 Building-Block Supply in Genetic Programming.- 10 Modularization by Multi-Run Frequency Driven Subtree Encapsulation.- 11 The Distribution of Reversible Functions is Normal.- 12 Doing Genetic Algorithms the Genetic Programming Way.- 13 Probalistic Model Building and Competent Genetic Programming.- 14 Automated Synthesis by Means of Genetic Programming Complex Structures Incorporating Reuse, Parameterized Reuse, Hierarchies, and Development.- 15 Industrial Strength Genetic Programming.- 16 Operator Choice and the Evolution of Robust Solution.- 17 A Hybrid GP-Fuzzy Approach for Reservoir Characterization.- 18 Enhanced Emerging Market Stock Selection.- 19 Three Fundamentals of the Biological Genetic Algorithm.

From the reviews: "This book contains 19 chapters that are based on respective research papers presented at the workshop ‘Genetic Program, Theory and Practice’. … The balanced combination of theoretical issues and application issues, along with the many new and interesting results described by the contributors make this book a useful source of up-to-date information on GP. The book will no doubt inspire new and old researchers and practitioners to push further the frontiers of GP theory and practice for the benefit of the international society." (Spyros Tzafestas, Journal of Intelligent and Robotic Systems, Vol. 45, 2006)