Logo - springer
Slogan - springer

Computer Science - Artificial Intelligence | From Fault Classification to Fault Tolerance for Multi-Agent Systems

From Fault Classification to Fault Tolerance for Multi-Agent Systems

Potiron, Katia, El Fallah Seghrouchni, Amal, Taillibert, Patrick

2013, VIII, 80 p. 19 illus.

Available Formats:

Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.

You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.

After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.


(net) price for USA

ISBN 978-1-4471-5046-6

digitally watermarked, no DRM

Included Format: PDF and EPUB

download immediately after purchase

learn more about Springer eBooks

add to marked items


Softcover (also known as softback) version.

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.


(net) price for USA

ISBN 978-1-4471-5045-9

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days

add to marked items

Faults are a concern for Multi-Agent Systems (MAS) designers, especially if the MAS are built for industrial or military use because there must be some guarantee of dependability. Some fault classification exists for classical systems, and is used to define faults. When dependability is at stake, such fault classification may be used from the beginning of the system’s conception to define fault classes and specify which types of faults are expected. Thus, one may want to use fault classification for MAS; however, From Fault Classification to Fault Tolerance for Multi-Agent Systems argues that working with autonomous and proactive agents implies a special analysis of the faults potentially occurring in the system. Moreover, the field of Fault Tolerance (FT) provides numerous methods adapted to handle different kinds of faults. Some handling methods have been studied within the MAS domain, adapting to their specificities and capabilities but increasing the large amount of FT methods. Therefore, unless being an expert in fault tolerance, it is difficult to choose, evaluate or compare fault tolerance methods, preventing a lot of developed applications from not only to being more pleasant to use but, more importantly, from at least being tolerant to common faults. From Fault Classification to Fault Tolerance for Multi-Agent Systems shows that specification phase guidelines and fault handler studies can be derived from the fault classification extension made for MAS. From this perspective, fault classification can become a unifying concept between fault tolerance methods in MAS.

Content Level » Research

Keywords » Agent Architecture - Autonomous Agent - Behavioral Faults - Fault Classification - Fault Tolerance - Multi-Agent System - Multi-Agent System Design

Related subjects » Artificial Intelligence - Control Engineering - Production & Process Engineering

Table of contents / Preface / Sample pages 

Popular Content within this publication 



Read this Book on Springerlink

Services for this book

New Book Alert

Get alerted on new Springer publications in the subject area of Artificial Intelligence (incl. Robotics).