Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence

Introduction: The Biological Perspective.- The Entities of Gene Expression Programming.- The Basic Gene Expression Algorithm.- The Basic GEA in Problem Solving.- Numerical Constants and the GEP-RNC Algorithm.- Automatically Defined Functions in Problem Solving.- Polynomial Induction and Time Series Prediction.- Parameter Optimization.- Decision Tree Induction.- Design of Neural Networks.- Combinatorial Optimization.- Evolutionary Studies.