Advances in genetic programming
By: edited by Kenneth E. Kinnear, Jr
Contributors: Kinnear, Kenneth E
Series: Complex adaptive systems
Publisher: MIT Press
Published: 1994
Place of publication: Cambridge, Mass
Language: eng
Number of pages: 518
Subjects: Computer programming
Description: Advances in Genetic Programming reports significant results in improving the power of genetic programming, presenting techniques that can be employed immediately in the solution of complex problems in many areas, including machine learning and the simulation of autonomous behavior. Popular languages such as C and C++ are used in manu of the applications and experiments, illustrating how genetic programming is not restricted to symbolic computing languages such as LISP.

Researchers interested in getting started in genetic programming will find information on how to begin, on what public-domain code is available, and on how to become part of the active genetic programming community via electronic mail.
Notes: "A Bradford book."

Includes bibliographical references and index
Table of contents: title: A perspective on the work in this book / Kenneth E. Kinnear, Jr.; title: Introduction to genetic programming / John R. Koza; title: The evolution of evolvability in genetic programming / Lee Altenberg; title: Genetic programming and emergent intelligence / Peter J. Angeline; title: Scalable learning in genetic programming using automatic function definition / John R. Koza; title: Alternatives in automatic function definition: a comparison of performance / Kenneth E. Kinnear, Jr.; title: The donut problem: scalability, generalization and breeding policies in genetic programming / Walter Alden Tackett, Aviram Carmi; title: Effects of locality in individual and population evolution / Patrik D'haeseleer, Jason Bluming; title: The evolution of mental models / Astro Teller; title: Evolution of obstacle avoidance behavior: using noise to promote robust solutions / Craig W. Reynolds; title: Pygmies and civil servants / Conor Ryan; title: Genetic programming using a minimum decsription length principle / Hitoshi Iba, Hugo de Garis, Taisuke Sato; title: Genetic programming in C++: implementation issues / Mike J. Keith, Martin C. Martin; title: A compiling genetic programming system that directly manipulates the machine code / Peter Nordin; title: Automatic generation of programs for crawling and walking / Graham Spencer; title: Genetic programming for the acquisition of double auction market strategies / Martin Andrews, Richard Prager; title: Two scientific applications of genetic programming: stack filters and non-linear equation fitting to chaotic data / Howard Oakley; title: The automatic generation of plans for a mobile robot via genetic programming with automatically defined functions / Simon G. Handley; title: Competitively evolving decision trees against fixed training cases for natural language processing / Eric V. Siegel; title: Cracking and co-evolving randomizers / Jan Jannink; title: Optimizing confidence of text classification by evolution of symbolic expressions / Brij Masand; title: Evolvable 3D modeling for model-based object recognition systems / Thang Nguyen, Thomas Huang; title: Automatically defined features: the simultaneous evolution of 2-dimensional feature detectors and an algorithm for using them / David Andre; title: Genetic micro programming of neural networks / Frédéric Gruau