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Robust Intelligent Systems

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Cover of 'Robust Intelligent Systems'

Table of Contents

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    Book Overview
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    Chapter 1 Robustness in Digital Hardware
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    Chapter 2 Multiagent-Based Fault Tolerance Management for Robustness
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    Chapter 3 A Two-Level Robustness Model for Self-Managing Software Systems
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    Chapter 4 Robustness in Network Protocols and Distributed Applications of the Internet
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    Chapter 5 Detecting Danger: The Dendritic Cell Algorithm
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    Chapter 6 Non-invasive Brain-Computer Interfaces for Semi-autonomous Assistive Devices
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    Chapter 7 Robust Learning of High-dimensional Biological Networks with Bayesian Networks
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    Chapter 8 Robustness in Nature as a Design Principle for Artificial Intelligence
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    Chapter 9 Feedback Structures as a Key Requirement for Robustness: Case Studies in Image Processing
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    Chapter 10 Exploiting Motor Modules in Modular Contexts in Humanoid Robotics
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    Chapter 11 Robustness as Key to Success for Space Missions
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    Chapter 12 Robust and Automated Space System Design
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    Chapter 13 Robust Bio-regenerative Life Support Systems Control
Attention for Chapter 7: Robust Learning of High-dimensional Biological Networks with Bayesian Networks
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Chapter title
Robust Learning of High-dimensional Biological Networks with Bayesian Networks
Chapter number 7
Book title
Robust Intelligent Systems
Published in
ADS, January 2008
DOI 10.1007/978-1-84800-261-6_7
Book ISBNs
978-1-84800-260-9, 978-1-84800-261-6
Authors

Andreas Nägele, Mathäus Dejori, Martin Stetter

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