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Authors: Gianfranco Lamperti and Marina Zanella

Affiliation: University of Brescia, Italy

ISBN: 978-989-8425-05-8

Keyword(s): Diagnosis, Discrete-event systems, Active systems, Communicating automata, Uncertainty, Lazyness.

Related Ontology Subjects/Areas/Topics: Applications of Expert Systems ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Enterprise Information Systems ; Industrial Applications of Artificial Intelligence ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Knowledge Engineering ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Knowledge-Based Systems Applications ; Software Engineering ; Symbolic Systems

Abstract: In society, laziness is generally considered as a negative feature, if not a capital fault. Not so in computer science, where lazy techniques are widespread, either to improve efficiency or to allow for computation of unbounded objects, such as infinite lists in modern functional languages. We bring the idea of lazy computation to the context of model-based diagnosis of active systems. Up to a decade ago, all approaches to diagnosis of discrete-event systems required the generation of the global system model, a technique that is impractical when the system is large and distributed. To overcome this limitation, a lazy approach was then devised in the context of diagnosis of active systems, which works with no need for the global system model. However, a similar drawback arose a few years later, when uncertain temporal observations were proposed. In order to reconstruct the system behavior based on an uncertain observation, an index space is generated as the determinization of a nondete rministic automaton derived from the graph of the uncertain observation, the prefix space. The point is that the prefix space and the index space suffer from the same computational difficulties as the system model. To confine the explosion of memory space when dealing with diagnosis of active systems with uncertain observations, a laziness-based, circular-pruning technique is presented. Experimental results offer evidence for the considerable effectiveness of the approach, both in space and time reduction. (More)

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Paper citation in several formats:
Lamperti G.; Zanella M. and (2010). DIAGNOSIS OF ACTIVE SYSTEMS BY LAZY TECHNIQUES.In Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8425-05-8, pages 171-180. DOI: 10.5220/0002855101710180

@conference{iceis10,
author={Gianfranco Lamperti and Marina Zanella},
title={DIAGNOSIS OF ACTIVE SYSTEMS BY LAZY TECHNIQUES},
booktitle={Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2010},
pages={171-180},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002855101710180},
isbn={978-989-8425-05-8},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - DIAGNOSIS OF ACTIVE SYSTEMS BY LAZY TECHNIQUES
SN - 978-989-8425-05-8
AU - Lamperti, G.
AU - Zanella, M.
PY - 2010
SP - 171
EP - 180
DO - 10.5220/0002855101710180

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