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Title: Swarm Intelligence: From Natural to Artificial Systems
Author: Eric Bonabeau, Marco Dorigo, and Guy Theraulaz
Publisher: Oxford
Year: 1999
ISBN: 0195131592
Abstract: Social insects--ants, bees, termites, and wasps--can be viewed as powerful problem-solving systems with sophisticated collective intelligence. Composed of simple interacting agents, this intelligence lies in the networks of interactions among individuals and between individuals and the environment. A fascinating subject, social insects are also a powerful metaphor for artificial intelligence, and the problems they solve--finding food, dividing labor among nestmates, building nests, responding to external challenges--have important counterparts in engineering and computer science. This book provides a detailed look at models of social insect behavior and how to apply these models in the design of complex systems. The book shows how these models replace an emphasis on control, preprogramming, and centralization with designs featuring autonomy, emergence, and distributed functioning. These designs are proving immensely flexible and robust, able to adapt quickly to changing environments and to continue functioning even when individual elements fail. In particular, these designs are an exciting approach to the tremendous growth of complexity in software and information. Swarm Intelligence draws on up-to-date research from biology, neuroscience, artificial intelligence, robotics, operations research, and computer graphics, and each chapter is organized around a particular biological example, which is then used to develop an algorithm, a multiagent system, or a group of robots. The book will be an invaluable resource for a broad range of disciplines.

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@Book{bonabeau99a,
  author =	 {Eric Bonabeau and Marco Dorigo and Guy Theraulaz},
  title =	 {Swarm Intelligence: From Natural to Artificial
                  Systems},
  publisher =	 {Oxford},
  year =	 1999,
  googleid =	 {-l2g5ldwWIQJ:scholar.google.com/},
  googleprint =	 {PvTDhzqMr7cC},
  abstract =	 {Social insects--ants, bees, termites, and wasps--can
                  be viewed as powerful problem-solving systems with
                  sophisticated collective intelligence. Composed of
                  simple interacting agents, this intelligence lies in
                  the networks of interactions among individuals and
                  between individuals and the environment. A
                  fascinating subject, social insects are also a
                  powerful metaphor for artificial intelligence, and
                  the problems they solve--finding food, dividing
                  labor among nestmates, building nests, responding to
                  external challenges--have important counterparts in
                  engineering and computer science. This book provides
                  a detailed look at models of social insect behavior
                  and how to apply these models in the design of
                  complex systems. The book shows how these models
                  replace an emphasis on control, preprogramming, and
                  centralization with designs featuring autonomy,
                  emergence, and distributed functioning. These
                  designs are proving immensely flexible and robust,
                  able to adapt quickly to changing environments and
                  to continue functioning even when individual
                  elements fail. In particular, these designs are an
                  exciting approach to the tremendous growth of
                  complexity in software and information. Swarm
                  Intelligence draws on up-to-date research from
                  biology, neuroscience, artificial intelligence,
                  robotics, operations research, and computer
                  graphics, and each chapter is organized around a
                  particular biological example, which is then used to
                  develop an algorithm, a multiagent system, or a
                  group of robots. The book will be an invaluable
                  resource for a broad range of disciplines.},
  keywords =     {multiagent biology ants},
  isbn = 	 {0195131592},
  cluster = 	 {9536495733790760442}
}
Last modified: Wed Mar 9 10:14:48 EST 2011