Description
Springer Linear Genetic Programming 2006 Edition by Markus F. Brameier Wolfgang Banzhaf
Linear Genetic Programming presents a variant of Genetic Programming that evolves imperative computer programs as linear sequences of instructions in contrast to the more traditional functional expressions or syntax trees. Typical GP phenomena such as non-effective code neutral variations and code growth are investigated from the perspective of linear GP. This book serves as a reference for researchers; it includes sufficient introductory material for students and newcomers to the field. Table of contents : Fundamental Analysis.- Basic Concepts of Linear Genetic Programming.- Characteristics of the Linear Representation.- A Comparison with Neural Networks.- Method Design.- Linear Genetic Operators I - Segment Variations.- Linear Genetic Operators II - Instruction Mutations.- Analysis of Control Parameters.- A Comparison with Tree-Based Genetic Programming.- Advanced Techniques and Phenomena.- Control of Diversity and Variation Step Size.- Code Growth and Neutral Variations.- Evolution of Program Teams.- Epilogue.