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Ant Colony Optimization (Bradford Books) Hardcover – June 4, 2004

ISBN-13: 978-0262042192 ISBN-10: 0262042193 Edition: First Edition, First Printing

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Ant Colony Optimization (Bradford Books) + Swarm Intelligence: From Natural to Artificial Systems (Santa Fe Institute Studies in the Sciences of Complexity) + Swarm Intelligence (The Morgan Kaufmann Series in Evolutionary Computation)
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Product Details

  • Series: Bradford Books
  • Hardcover: 319 pages
  • Publisher: A Bradford Book; First Edition, First Printing edition (June 4, 2004)
  • Language: English
  • ISBN-10: 0262042193
  • ISBN-13: 978-0262042192
  • Product Dimensions: 7 x 0.8 x 9 inches
  • Shipping Weight: 1.5 pounds (View shipping rates and policies)
  • Average Customer Review: 4.6 out of 5 stars  See all reviews (8 customer reviews)
  • Amazon Best Sellers Rank: #1,267,549 in Books (See Top 100 in Books)

Editorial Reviews

Review

"Inspired by the remarkable ability of social insects to solve problems, Dorigo and Stützle introduce highly creative new technological design principles for seeking optimized solutions to extremely difficult real-world problems, such as network routing and task scheduling. This is essential reading not only for those working in artificial intelligence and optimization, but for all of us who find the interface between biology and technology fascinating."--Iain D. Couzin, University of Oxford

About the Author

Marco Dorigo is a research director of the FNRS, the Belgian National Funds for Scientific Research, and co-director of IRIDIA, the artificial intelligence laboratory of the Université Libre de Bruxelles. He is the inventor of the ant colony optimization metaheuristic. His current research interests include swarm intelligence, swarm robotics, and metaheuristics for discrete optimization. He is the Editor-in-Chief of Swarm Intelligence, and an Associate Editor or member of the Editorial Boards of many journals on computational intelligence and adaptive systems. Dr. Dorigo is a Fellow of the ECCAI and of the IEEE. He was awarded the Italian Prize for Artificial Intelligence in 1996, the Marie Curie Excellence Award in 2003, the Dr. A. De Leeuw-Damry-Bourlart award in applied sciences in 2005, the Cajastur "Mamdani" International Prize for Soft Computing in 2007, and an ERC Advanced Grant in 2010.

Thomas Stützle is Assistant Professor in the Computer Science Department at Darmstadt University of Technology.

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Most Helpful Customer Reviews

23 of 24 people found the following review helpful By wiredweird HALL OF FAMETOP 1000 REVIEWER on April 27, 2005
Format: Hardcover Verified Purchase
Being an ant isn't very complex, but it's a daily fight for life. The losers in that fight don't count, but the winners get to vote.

That is the basis of ant colony optimization. There are many parts to the idea, all of them very simple. First, there are many routes to the goal (food, if you're an ant) - some are better, some worse, you don't know which are which in advance, and the answer may change over time. Second, it's a random search. If you find any answer at all, no matter how convoluted, you get to vote on your route. Third, there are many other ants, all voting. Any leg of a trip that is heavily followed must be part of a good route, and gets many votes. There are details, but that's about it.

Chapters 1-3 are the most readable, and convey the basic spirit of the family of algorithms. Ch. 4-6 will drag a bit, for the general reader, but go into significant detail about the ant algorithm and specific applications.

Ch. 7 ends the book with a warm, informal discussion of the algorithm's history and some delightful variations. Dorigo, the principal author and founder of the ant school, uses this chapter to express his pure joy at having found such a wonderful thing, and at the similar approaches that others have also found.

The approach has some real limits. For example, it can solve only problems that look like finding the shortest route. The good news is that a wide range of unlikely problems can all be cast in these terms. The better news is that, given the many variations available, some form of the 'stigmergic' approach will probably solve any problem in that range. Best of all, though, is the sheer cleverness and the sincere appreciation expressed by the authors.

Nature is economical, but a brilliant problem solver. This is written by someone who as able to listen in on one of the lessons.

//wiredweird
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14 of 15 people found the following review helpful By Markus Waibel on October 4, 2004
Format: Hardcover
Fifteen years after the elegant double-bridge experiments by Deneubourg et al. that formed the basis of the Ant Colony Optimization algorithm, Marco Dorigo, the inventor of ACO, and Thomas Stützle, an expert on stochastic local search methods, have pooled their knowledge to summarize the current state of the art.

This book gives a well paced introduction to ACO, describes its use in various optimization problems and gives interesting examples of its applications in industry. Explanations are clear and concise and, with the exception of a few well defined technical terms, free of scientific jargon. It is a pleasure to read for everyone with an interest in optimization theory. However, if you are looking for a book that celebrates the beauty of nature's problem solving capabilities, you are better of with "Swarm Intelligence" or Flake's "Computational Beauty of Nature". The initial idea of ACO may be bio-inspired, but this book has a crystal clear focus of the computational considerations in optimization theory.
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9 of 11 people found the following review helpful By Wagner F. Sacco on September 3, 2004
Format: Hardcover
This book is a fine compilation of what have been done with the Ant Colony paradigm so far. Highly readable, even for people without previous experience in the field of optimization.
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1 of 1 people found the following review helpful By Parker W. Snapp on September 27, 2008
Format: Hardcover Verified Purchase
Ant Colony Optimization focuses on the fact that ants foraging for food will quickly form a trail that is the shortest possible ditance betwen the food and home. Rach ant follows the scent trail laid on a path by previous travelers and adds its own pheromone to the scent, both going and coming. With a choice, ants tend to follow the strongest scent. Of a pioneer pair, the one choosing the shortest path will make the round trip before the other. Each pheromone trace evaporates in time, but an ant's antenna can detetct the slightest trace. That is a simplification of the introductory chapters of the book. The "pheromone trail" scheme is used to devise "artificial ant" which then takes part in the comnstruction of powerful ant algorithms for solving intractable problems such as the classical "Traveling Salesman" and other routing problems. The book is a complete text for a college course, with a large bibliography and many internal references to sources on the Internet. It is well written, with pseudo code showing how each algorithm can form computer programs. I can't evaluate the difficulty, but for me the math in later chapters is above my reach, but gratifying, nevertheless.
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Ant Colony Optimization (Bradford Books)
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