Biologically-Inspired Collaborative Computing - IFIP 20th World Computer Congress, Second IFIP TC 10 International Conference on Biologically-Inspired Collaborative Computing, September 8-9, 2008, Milano, Italy (Hardcover, 2008 ed.)


"Look deep into nature and you will understand everything better." advised Albert Einstein. In recent years, the research communities in Computer Science, Engineering, and other disciplines have taken this message to heart, and a relatively new field of "biologically-inspired computing" has been born. Inspiration is being drawn from nature, from the behaviors of colonies of ants, of swarms of bees and even the human body. This new paradigm in computing takes many simple autonomous objects or agents and lets them jointly perform a complex task, without having the need for centralized control. In this paradigm, these simple objects interact locally with their environment using simple rules. Applications include optimization algorithms, communications networks, scheduling and decision making, supply-chain management, and robotics, to name just a few. There are many disciplines involved in making such systems work: from artificial intelligence to energy aware systems. Often these disciplines have their own field of focus, have their own conferences, or only deal with specialized s- problems (e.g. swarm intelligence, biologically inspired computation, sensor networks). The Second IFIP Conference on Biologically-Inspired Collaborative Computing aims to bridge this separation of the scientific community and bring together researchers in the fields of Organic Computing, Autonomic Computing, Self-Organizing Systems, Pervasive Computing and related areas. We are very pleased to have two very important keynote presentations: Swarm Robotics: The Coordination of Robots via Swarm Intelligence Principles by Marco Dorigo (Universite Libre de Bruxelles, Belgium), of which an abstract is included in this volume.

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"Look deep into nature and you will understand everything better." advised Albert Einstein. In recent years, the research communities in Computer Science, Engineering, and other disciplines have taken this message to heart, and a relatively new field of "biologically-inspired computing" has been born. Inspiration is being drawn from nature, from the behaviors of colonies of ants, of swarms of bees and even the human body. This new paradigm in computing takes many simple autonomous objects or agents and lets them jointly perform a complex task, without having the need for centralized control. In this paradigm, these simple objects interact locally with their environment using simple rules. Applications include optimization algorithms, communications networks, scheduling and decision making, supply-chain management, and robotics, to name just a few. There are many disciplines involved in making such systems work: from artificial intelligence to energy aware systems. Often these disciplines have their own field of focus, have their own conferences, or only deal with specialized s- problems (e.g. swarm intelligence, biologically inspired computation, sensor networks). The Second IFIP Conference on Biologically-Inspired Collaborative Computing aims to bridge this separation of the scientific community and bring together researchers in the fields of Organic Computing, Autonomic Computing, Self-Organizing Systems, Pervasive Computing and related areas. We are very pleased to have two very important keynote presentations: Swarm Robotics: The Coordination of Robots via Swarm Intelligence Principles by Marco Dorigo (Universite Libre de Bruxelles, Belgium), of which an abstract is included in this volume.

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Product Details

General

Imprint

Springer-Verlag New York

Country of origin

United States

Series

IFIP Advances in Information and Communication Technology, 268

Release date

August 2008

Availability

Supplier out of stock. If you add this item to your wish list we will let you know when it becomes available.

First published

2008

Editors

, , ,

Dimensions

235 x 155 x 15mm (L x W x T)

Format

Hardcover

Pages

247

Edition

2008 ed.

ISBN-13

978-0-387-09654-4

Barcode

9780387096544

Categories

LSN

0-387-09654-X



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