Evolutionary Algorithms
Lawrence D. Davis
Reading Time
at 250 WPM4h 53m
The average reader, reading at a speed of 250 WPM, would take 4h 53m to read Evolutionary Algorithms.
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10
days at 30 min/day
293
total minutes
Evolutionary Algorithms
by Lawrence D. Davis, Kenneth De Jong, Michael D. Vose
Published
2012
Publisher
Springer New York
Pages
293
ISBN-13
9781461271857
Description
The IMA Workshop on Evolutionary Algorithms brought together many of the top researchers in the area of Evolutionary Computation for a week of intensive interaction. The field of Evolutionary Computation has developed significantly over the past 30 years and today consists of a variety of subfields such as genetic algorithms, evolution strategies, evolutionary programming, and genetic programming, each with its own algorithmic perspectives and goals. The workshop did a great deal to clarify the current state of the theory of Evolutionary Algorithms. The existing theory might be characterized as deriving from two principal approaches. There is a high level macro-theory that looks at the processing of "building blocks" and "schemata" that are shared by many good solutions when searching a problem space. There is also a low level micro-theory that builds exact Markov models of the search process. It is sometimes hard for researchers working at such different levels of abstraction to interact. The IMA workshop allowed researchers working at these different levels to present their points of view and to move toward common ground. There was real progress in communication between theorists and practitioners in the evolutionary computation field. Speakers presented applications across a wide range of problem areas. In some of those cases, theoretically motivated methods work quite well. In other cases, practitioners used domain-based methods to obtain better performance than could be achieved by using a "pure" evolutionary algorithm. Individuals on both sides went away with a better appreciation of the successes and failures of current theory.
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Frequently Asked Questions
How many pages are in Evolutionary Algorithms?
This edition of Evolutionary Algorithms has approximately 293 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 Evolutionary Algorithms?
For most readers, Evolutionary Algorithms typically takes between 6h 6m and 4h 4m to complete. This is based on the book's length of approximately 73,250 words and common reading speeds.
Here's a detailed breakdown: • Continuous reading at 250 WPM: approximately 4h 53m of focused reading • Casual reading (30 minutes/day): you could finish in roughly 10 days • Estimated word count: 73,250 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 Evolutionary Algorithms?
The estimated word count for Evolutionary Algorithms is approximately 73,250 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 Evolutionary Algorithms?
Evolutionary Algorithms was written by Lawrence D. Davis, Kenneth De Jong, Michael D. Vose.
When was Evolutionary Algorithms published?
The publication date for this specific edition is 2012. The original work may have been published on a different date.