Genetic programming
Julian F. Miller
Reading Time
at 250 WPM6h 30m
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13
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390
total minutes
Genetic programming
by Julian F. Miller, Marco Tomassini, Conor Ryan
Published
2005
Publisher
Springer London, Limited
Pages
390
ISBN-13
9783540319894
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>
Frequently Asked Questions
How many pages are in Genetic programming?
This edition of Genetic programming has approximately 390 pages. Please note, this is an estimate and the exact page count can vary between hardcover, paperback, and e-book versions.
How long does it take to read Genetic programming?
For most readers, Genetic programming typically takes between 8h 8m and 5h 25m to complete. This is based on the book's length of approximately 97,500 words and common reading speeds.
Here's a detailed breakdown: • Continuous reading at 250 WPM: approximately 6h 30m of focused reading • Casual reading (30 minutes/day): you could finish in roughly 13 days • Estimated word count: 97,500 words
Your individual reading time will vary based on your personal reading pace, the amount of daily reading time, and your familiarity with the subject matter.
What is the word count of Genetic programming?
The estimated word count for Genetic programming is approximately 97,500 words. This figure is calculated using industry-standard methods that consider genre-specific word density patterns, typical formatting and layout characteristics, and standard words-per-page ratios for published books.
This is an approximation — actual word count may vary based on font size, formatting, edition, and the presence of illustrations or charts.
Who is the author of Genetic programming?
Genetic programming was written by Julian F. Miller, Marco Tomassini, Conor Ryan.
When was Genetic programming published?
The publication date for this specific edition is 2005. The original work may have been published on a different date.