Cover image for Robust intelligent systems
Title:
Robust intelligent systems
Publication Information:
London : Springer, 2008
Physical Description:
xi, 299 p. : ill. ; 25 cm.
ISBN:
9781848002609
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30000010193858 Q335 R64 2008 Open Access Book Book
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Summary

Summary

Our time recognizes robustness as an important, all-pervading feature in the world around us. Despite its omnipresence, robustness is not entirely understood, rather dif?cult to de?ne, and, despite its obvious value in many situations, rather dif?cult to achieve. One of the goals of this edited book is to report on the topic of robustness from a variety and diverse range of ?elds and perspectives. We are interested, for instance, in fundamental strategies nature applies to make systems robust--and arguably "intelligent"--and how these strategies may hold as general design principles in modern technology. A particular focus is on computer-based systems and appli- tions. This in mind, the book has four main sections: Part I has a look at robustness in terms of underlying technologies and infrastr- tures upon which many computer-based "intelligent" systems reside and inves- gates robustness on the hardware and software level, but also in larger environments such as the Internet and self-managing systems. The contributions in Part II target robustness in research areas that are inspired by biology, including brain-computer interfaces, biological networks, and biological immune systems, for example. Part III involves the exciting ?eld of arti?cial intelligence. The chapters here discuss the value of robustness as a general design principle for arti?cial intelligence, stressing its potential in areas such as humanoid robotics and image processing.


Table of Contents

Roger Woods and Gaye LightbodyRosa Laura Zavala Gutierrez and Michael HuhnsDavid Bustard and Roy SterrittJurgen Vogel and Jorg WidmerJulie Greensmith and Uwe Aickelin and Steve CayzerBernhard Graimann and Brendan Allison and Christian Mandel and Thorsten Luth and Diana Valbuena and Axel GraserAndreas Nagele and Mathaus Dejori and Martin StetterAlfons SchusterAxel Graser and Danijela RisticFrancesco Nori and Giorgio Metta and Giulio SandiniOlaf Maibaum and Sergio Montenegro and Thomas TerzibaschianMartin Fuchs and Daniela Girimonte and Dario Izzo and Arnold NeumaierJordi Duatis and Cecilio Angulo and Vicenc Puig and Pere Ponsa
Part I Robustness in Computer Hardware, Software, Networks, and Protocols
1 Robustness in Digital Hardwarep. 3
2 Multiagent-Based Fault Tolerance Management for Robustnessp. 23
3 A Two-Level Robustness Model for Self-Managing Software Systemsp. 43
4 Robustness in Network Protocols and Distributed Applications of the Internetp. 61
Part II Robustness in Biology Inspired Systems
5 Detecting Danger: The Dendritic Cell Algorithmp. 89
6 Non-invasive Brain-Computer Interfaces for Semi-autonomous Assistive Devicesp. 113
7 Robust Learning of High-dimensional Biological Networks with Bayesian Networksp. 139
Part III Robustness in Artificial Intelligence Systems
8 Robustness in Nature as a Design Principle for Artificial Intelligencep. 165
9 Feedback Structures as a Key Requirement for Robustness: Case Studies in Image Processingp. 189
10 Exploiting Motor Modules in Modular Contexts in Humanoid Roboticsp. 209
Part IV Robustness in Space Applications
11 Robustness as Key to Success for Space Missionsp. 233
12 Robust and Automated Space System Designp. 251
13 Robust Bio-regenerative Life Support Systems Controlp. 273
Indexp. 297