Genetic Programming and Data Structures Genetic Programming + Data Structures = Automatic Programming!

Langdon, William B.

ISBN 10: 0792381351 / ISBN 13: 9780792381358

Published by Kluwer Academic Publishers, Boston, Dordrecht, London, 1998

About this Item

First Edition. xiv, 278, [2] pages. 8vo. Pictorial boards. Ex-library Rowland Institute for Science with spine label, ink stamps on several pages and textblock edges, and rear library pocket. Spine and portions of boards sun faded. Spine shelf leaned. Clean internally. Boards. "Founded in 1981 as the "last experiment" of the accomplished scientist and entrepreneur Edwin H. Land, the Rowland Institute has developed a distinguished reputation for multi- and interdisciplinary research, especially in evolving areas at the junction of traditional fields such as physics and biology." (Harvard Gazette, 2002). "The Rowland Institute at Harvard, formerly the Rowland Institute for Science, was founded by Edwin H. Land (founder of Polaroid Corporation) as a nonprofit, privately endowed basic research organization in 1980. The institute merged with Harvard University on July 1, 2002. The Rowland Institute is dedicated to experimental science across a wide range of disciplines. Research subjects at the institute includes chemistry, physics and biology, and focus on interdisciplinary work and the development of new experimental tools." (Wikipedia) The Rowland Institute for Science library was dismantled when the Rowland Institute moved from it's original home at 100 Edwin H Land Blvd, Cambridge MA to its new home on Oxford St at Harvard. Seller Inventory # 29489

Bibliographic Details

Title: Genetic Programming and Data Structures ...

Publisher: Kluwer Academic Publishers, Boston, Dordrecht, London

Publication Date: 1998

Binding: Boards

Condition: Very Good

Edition: First Edition.

About this title

Synopsis:

Computers that `program themselves' has long been an aim of computer scientists. Recently genetic programming (GP) has started to show its promise by automatically evolving programs. Indeed in a small number of problems GP has evolved programs whose performance is similar to or even slightly better than that of programs written by people. The main thrust of GP has been to automatically create functions. While these can be of great use they contain no memory and relatively little work has addressed automatic creation of program code including stored data. This issue is the main focus of Genetic Programming, and Data Structures: Genetic Programming + Data Structures = Automatic Programming!.
This book is motivated by the observation from software engineering that data abstraction (e.g., via abstract data types) is essential in programs created by human programmers. This book shows that abstract data types can be similarly beneficial to the automatic production of programs using GP.
Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming! shows how abstract data types (stacks, queues and lists) can be evolved using genetic programming, demonstrates how GP can evolve general programs which solve the nested brackets problem, recognises a Dyck context free language, and implements a simple four function calculator. In these cases, an appropriate data structure is beneficial compared to simple indexed memory. This book also includes a survey of GP, with a critical review of experiments with evolving memory, and reports investigations of real world electrical network maintenance scheduling problems that demonstrate that Genetic Algorithms can find low cost viable solutions to such problems.
Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming! should be of direct interest to computer scientists doing research on genetic programming, genetic algorithms, data structures, and artificial intelligence. In addition, this book will be of interest to practitioners working in all of these areas and to those interested in automatic programming.

Review:

`The book is nicely produced ... and well illustrated. The text is well written and is easy to read and understand. The concepts in genetic programming are well presented, as are those in genetic algorithms. The references are selected to be useful. People of a non-mathematical disposition will find few problems in reading this book.'
Robotica, 17 (1999)