This book 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. It is one of the few books that deals solely with Linear GP and contains many concrete, experimental results. The book serves as a reference for researchers, but also contains sufficient introduction for students and those who are new to the field.

One of the few books that deals solely with linear GP and contains a number of concrete, experimental results Methods and analysis techniques are specifically adapted to the LGP approach, analyzing LGP in more detail while concentrating on principle characteristics of an imperative program structure in comparison to a tree representation Includes supplementary material: sn.pub/extras

Autorentext

Markus Brameier received a PhD degree in Computer Science from the Department of Computer Science at University of Dortmund, Germany,in 2004. From 2003 to 2004 he was a postdoctoral fellow at the Stockholm Bioinformatics Center (SBC), a collaboration between Stockholm University, the Royal Institute of Technology, and Karolinska Institute, in Sweden. Currently he is Assistant Professor at the Bioinformatics Research Center (BiRC) of the University of Aarhus in Denmark. His primary research interests are in bioinformatics and genetic programming. Wolfgang Banzhaf is a professor of Computer Science at the Department of Computer Science of Memorial University of Newfoundland, Canada, and head of the department since 2003. Prior to that, he served for 10 years as Associate Professor for Applied Computer Science in the Department of Computer Science at University of Dortmund, Germany. From 1989 to 1993 he was a researcher with Mitsubishi Electric Corp.,first in MELCO's Central Research Lab in Japan, then in the United States at Mitsubishi Electric Research Labs Inc., Cambridge, MA. Between 1985 and 1989 he was a postdoc in the Department of Physics, University of Stuttgart, Germany. He holds a PhD in Physics from the University of Karlruhe in Germany. His research interests are in the field of artificial evolution and self-organization studies. He has recently become more involved with bioinformatics.

Inhalt
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.