Linear Genetic Programming
By Markus F. Brameier and Dr. Wolfgang Banzhaf
Imagine a world in which computers breed programs. Genetic Programming (GP), a methodology based on Darwin’s theory of natural evolution, uses this paradigm to arrive at computer-evolved algorithms.
Linear Genetic Programming presents a variant of this methodology that automatically evolves imperative computer programs as linear sequences of instructions, much in line with the material most programmers work with.
The primary characteristics of this linear program structure is exploited to achieve acceleration of both execution time and evolutionary progress of the genetic material.
Online analysis and optimization of program code are applied to lead to more efficient techniques and contribute to a better understanding of the underlying method.
Typical GP phenomena, such as non-effective code, neutral variations, and code growth are investigated from the perspective of linear GP.
This book is intended to serve as a reference for researchers. It also contains sufficient introductory material for students and those new to the field.
|Dr. Wolfgang Banzhaf
Dr. Wolfgang Banzhaf is professor in the Department of Computer Science and head of the department since 2003.
Before arriving at Memorial, he served as associate professor for applied computer science at the University of Dortmund, Germany. Until 1993, he was a researcher with Mitsubishi Electric Corp, in Japan and the US.
He holds a PhD in Physics from the University of Karlruhe in Germany.
His research interests are in the field of biologically-inspired methods of computing and he recently become more involved with bioinformatics.
Linear Genetic Programming is published by Springer.