Genetic Programming
4th European Conference, EuroGP 2001 Lake Como, Italy, April 18-20, 2001 Proceedings (Lecture Notes in Computer Science)
1 edition
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Contributions
- Julian Miller (Editor) - Contributor
- Marco Tomassini (Editor) - Contributor
- Pier Luca Lanzi (Editor) - Contributor
- Conor Ryan (Editor) - Contributor
- Andrea G.B. Tettamanzi (Editor) - Contributor
and 1 more
- William B. Langdon (Editor) - Contributor
Publication
2001-05-11 - Springer
Language
English
Word Count
96,000 words, Guess
Page Count
384 pages
Physical Format
Paperback
Identifiers
- Internet Archivegeneticprogrammi00mill
- Internet Archivespringer_10.1007-3-540-45355-5
- ISBN-103540418997
- ISBN-139783540418993
- Goodreads1381868
and 4 more
- Library of Congress Control Number2001020853
- OCLC Control Number46502093
- Better World Books9783540418993
- Open LibraryOL9827308M
Classifications
- LCCQA76.623 .E94 2001
- LCCQA75.5-76.95
Description
Genetic Programming: 4th European Conference, EuroGP 2001 Lake Como, Italy, April 18–20, 2001 Proceedings<br />Author: Julian Miller, Marco Tomassini, Pier Luca Lanzi, Conor Ryan, Andrea G. B. Tettamanzi, William B. Langdon<br /> Published by Springer Berlin Heidelberg<br /> ISBN: 978-3-540-41899-3<br /> DOI: 10.1007/3-540-45355-5<br /><br />Table of Contents:<p></p><ul><li>Heuristic Learning Based on Genetic Programming </li><li>Evolving Color Constancy for an Artificial Retina </li><li>Adaptive Genetic Programming Applied to New and Existing Simple Regression Problems </li><li>An Evolutionary Approach to Automatic Generation of VHDL Code for Low-Power Digital Filters </li><li>Studying the Influence of Communication Topology and Migration on Distributed Genetic Programming </li><li>CAGE: A Tool for Parallel Genetic Programming Applications </li><li>Ripple Crossover in Genetic Programming </li><li>Evolving Receiver Operating Characteristics for Data Fusion </li><li>An Adaptive Mapping for Developmental Genetic Programming </li><li>A Schema Theory Analysis of the Evolution of Size in Genetic Programming with Linear Representations </li><li>Exact Schema Theorems for GP with One-Point and Standard Crossover Operating on Linear Structures and Their Application to the Study of the Evolution of Size </li><li>General Schema Theory for Genetic Programming with Subtree-Swapping Crossover </li><li>Evolving Modules in Genetic Programming by Subtree Encapsulation </li><li>Evolution of Affine Transformations and Iterated Function Systems Using Hierarchical Evolution Strategy </li><li>Evolving Turing Machines for Biosequence Recognition and Analysis </li><li>Neutrality and the Evolvability of Boolean Function Landscape </li><li>Polymorphism and Genetic Programming </li><li>Programmable Smart Membranes: Using Genetic Programming to Evolve Scalable Distributed Controllers for a Novel Self-Reconfigurable Modular Robotic Application </li><li>A GP Artificial Ant for image processing: preliminary experiments with EASEA. </li><li>Feature Extraction for the k-Nearest Neighbour Classifier with Genetic Programming</li></ul>
First Sentence
Genetic programming (GP) is a fast developing field which aims at evolving a population of computer codes towards a program that solves a given problem [Koz92].
Subjects
Topics
Other Editions
- Genetic Programming: 4th European Conference, EuroGP 2001 Lake Como, Italy, April 18-20, 2001 Proceedings (Lecture Notes in Computer Science)
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