Linear Genetic Programming
Buch in deiner Nähe kaufen
Beschreibung
Linear Genetic Programming examines the evolution of imperative computer programs written as linear sequences of instructions. In contrast to functional expressions or syntax trees used in traditional Genetic Programming (GP), Linear Genetic Programming (LGP) employs a linear program structure as genetic material whose primary characteristics are exploited to achieve acceleration of both execution time and evolutionary progress. Online analysis and optimization of program code lead to more efficient techniques and contribute to a better understanding of the method and its parameters. In particular, the reduction of structural variation step size and non-effective variations play a key role in finding higher quality and less complex solutions. This volume investigates typical GP phenomena such as non-effective code, neutral variations and code growth from the perspective of linear GP.
The text is divided into three parts, each of which details methodologies and illustrates applications. Part I introduces basic concepts of linear GP and presents efficient algorithms for analyzing and optimizing linear genetic programs during runtime. Part II explores the design of efficient LGP methods and genetic operators inspired by the results achieved in Part I. Part III investigates more advanced techniques and phenomena, including effective step size control, diversity control, code growth, and neutral variations.
The book provides a solid introduction to the field of linear GP, as well as a more detailed, comprehensive examination of its principles and techniques. Researchers and students alike are certain to regard this text as an indispensable resource.
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
Autor*in
Markus F. Brameier
Themen in »Linear Genetic Programming«
Step Size Control Syntax algorithms code growth diversity control evolutionary algorithm genetic algorithms genetic operators genetic programming learning linear genetic programming machine learning neutral variations optimization programming
Stimmen zu »Linear Genetic Programming«
From the reviews:
"This is a very good book. It provides a well organized description of linear genetic programming (LGP). Much material, previously only available in research papers, has been consolidated, reorganized and extended for this book. … This book is primarily for the evolutionary computing researcher … . Post graduate students in genetic programming should read this book … . The book should be in university libraries. Considering the cost of many books these days this one is very well priced for its size and content." (Vic Ciesielski, Genetic Programming and Evolvable Machines, Vol. 9, 2008)
"This book addresses a subfield of genetic programming, where solutions are represented by a sequence of instructions in an imperative programming language, such as C. Genetic programming is an iterative search algorithm based loosely on the concepts of biological evolution. … Brameier and Banzhaf present a thorough overview that will serve as an excellent resource for graduate students, academics, and practitioners, who choose to work with linear genetic programming." (Steven Gustafson, ACM Computing Reviews, Vol. 49 (8), August, 2008)
()