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Illustrating Evolutionary Computation with Mathematica, Christian Jacob 2001-EXC-
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eBay-Artikelnr.:277093719101
Artikelmerkmale
- Artikelzustand
- Artist
- Christian Jacob
- ISBN
- 1558606378
- Release Title
- Illustrating Evolutionary Computation with Mathematica, (The M...
- Book Title
- Illustrating Evolutionary Computation with Mathematica, (The M...
- Educational Level
- Adult & Further Education
- Personalized
- No
- Features
- Illustrated
- Level
- Advanced, Proficiency, Technical
- Country/Region of Manufacture
- Canada
Über dieses Produkt
Product Identifiers
Publisher
Elsevier Science & Technology
ISBN-10
1558606378
ISBN-13
9781558606371
eBay Product ID (ePID)
1742492
Product Key Features
Number of Pages
578 Pages
Publication Name
Illustrating Evolutionary Computation with Mathematica
Language
English
Publication Year
2001
Subject
Programming / Algorithms, Intelligence (Ai) & Semantics
Type
Textbook
Subject Area
Computers
Series
The Morgan Kaufmann Series in Artificial Intelligence Ser.
Format
Hardcover
Dimensions
Item Height
1.3 in
Item Weight
42.5 Oz
Item Length
9.2 in
Item Width
7.4 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
00-048385
Reviews
"This book provides a thorough survey of evolutionary computation techniques, including genetic algorithms, genetic programming, evolutionary programming, and evolution strategies. The author uses mathematica to illustrate the examples. If you know mathematica, you'll find this unique angle to be invaluable, but even if you don't know mathematica, if you're familiar with any programming languages, or matlab, maple, etc., you should be able to make the connections. The figures in this book have to be the most illustrative examples offered in any evolutionary computation text to date. The text is easy to read and very informative." -- Review in IEEE Computer Magazine, June issue.*5* star amazon.com review
Dewey Edition
21
Illustrated
Yes
Dewey Decimal
006.3/1
Table Of Content
Part 1: Fascinating Evolution Part 2: Evolutionary Computation Part 3: If Darwin was a Programmer Part 4: Evolution of Developmental Programs
Synopsis
An essential capacity of intelligence is the ability to learn. An artificially intelligent system that could learn would not have to be programmed for every eventuality; it could adapt to its changing environment and conditions just as biological systems do. Illustrating Evolutionary Computation with Mathematica introduces evolutionary computation to the technically savvy reader who wishes to explore this fascinating and increasingly important field. Unique among books on evolutionary computation, the book also explores the application of evolution to developmental processes in nature, such as the growth processes in cells and plants. If you are a newcomer to the evolutionary computation field, an engineer, a programmer, or even a biologist wanting to learn how to model the evolution and coevolution of plants, this book will provide you with a visually rich and engaging account of this complex subject., An essential capacity of intelligence is the ability to learn. An artificially intelligent system that could learn would not have to be programmed for every eventuality; it could adapt to its changing environment and conditions just as biological systems do. Illustrating Evolutionary Computation with Mathematica introduces evolutionary computation to the technically savvy reader who wishes to explore this fascinating and increasingly important field. Unique among books on evolutionary computation, the book also explores the application of evolution to developmental processes in nature, such as the growth processes in cells and plants. If you are a newcomer to the evolutionary computation field, an engineer, a programmer, or even a biologist wanting to learn how to model the evolution and coevolution of plants, this book will provide you with a visually rich and engaging account of this complex subject. * Introduces the major mechanisms of biological evolution. * Demonstrates many fascinating aspects of evolution in nature with simple, yet illustrative examples. * Explains each of the major branches of evolutionary computation: genetic algorithms, genetic programming, evolutionary programming, and evolution strategies. * Demonstrates the programming of computers by evolutionary principles using Evolvica, a genetic programming system designed by the author. * Shows in detail how to evolve developmental programs modeled by cellular automata and Lindenmayer systems. * Provides Mathematica notebooks on the Web that include all the programs in the book and supporting animations, movies, and graphics.
LC Classification Number
QA76.618.J3313 2001
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