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Swarm Intelligence: From Natural to Artificial Systems (Santa Fe Institute Studies in the Sciences of Complexity)
 
 

Swarm Intelligence: From Natural to Artificial Systems (Santa Fe Institute Studies in the Sciences of Complexity) [Kindle Edition]

Eric Bonabeau , Marco Dorigo , Guy Theraulaz
5.0 out of 5 stars  See all reviews (3 customer reviews)

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Product Description

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.

About the Author

Eric Bonabeau is at Santa Fe Institute. Marco Dorigo is at Free University of Brussels.

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3 of 5 people found the following review helpful
Format:Paperback
If you are into reinforcement learning and looking for an alternate meta heruistic try this book. This is one of the few books that you can find in this area. It gives a brief description of Ant colony optimisation which is an agent based optimisation method that is influenced from emergent behaviour of simple and individual ants in the nature. I was particularly interested with antnet routing algorithm which is explained in detail in one chapter.
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8 of 18 people found the following review helpful
By Philip
Format:Paperback
Very good introduction examines how swarm intelligence happens in the real world and then distills some of the processes that can be created to enable artificial swarms.
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4 of 10 people found the following review helpful
By Brains VINE™ VOICE
Format:Paperback
When I bought this book I was leafing through it and a colleague asked me "do you understand all that stuff?". Looking at a page of degree level maths formulas, I had to confess that I didn't but I did say "No, but it makes me look intelligent.".

This subject does interest me, but I did A-level maths a few years ago and it is difficult to follow some of the more complex algorithms because I'm a little rusty. However, the book is well written and covers the topic in a thorough and well organised way.

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Popular Highlights

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&quote;
Indirect interactions are more subtle: two individuals interact indirectly when one of them modifies the environment and the other responds to the new environment at a later time. Such an interaction is an example of stigmergy. &quote;
Highlighted by 4 Kindle users
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However, it does provide a general mechanism that relates individual and colony-level behaviors: individual behavior modifies the environment, which in turn modifies the behavior of other individuals. &quote;
Highlighted by 3 Kindle users
&quote;
Self-organization is a set of dynamical mechanisms whereby structures appear at the global level of a system from interactions among its lower-level components. &quote;
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