Linear Genetic Programming (Genetic and Evolutionary Computation) [Hardcover]

Markus F. Brameier (Author), Wolfgang Banzhaf (Author)

Book Description

Publication Date: December 11, 2006 | ISBN-10: 0387310290 | ISBN-13: 978-0387310299 | Edition: 1

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.

Editorial Reviews

Review

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)

From the Back Cover

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.

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Product Details

• Hardcover: 332 pages
• Publisher: Springer; 1 edition (December 11, 2006)
• Language: English
• ISBN-10: 0387310290
• ISBN-13: 978-0387310299
• Product Dimensions: 6.5 x 9.1 x 1.1 inches
• Shipping Weight: 1.4 pounds (View shipping rates and policies)
• Amazon Best Sellers Rank: #2,997,296 in Books (See Top 100 in Books)
  • #85 in Books > Computers & Technology > Programming > Algorithms > Genetic

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