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Authors: Jan Kantert 1 ; Sven Tomforde 2 ; Christian Müller-Schloer 1 ; Sarah Edenhofer 3 and Bernard Sick 2

Affiliations: 1 Leibniz University Hanover, Germany ; 2 University of Kassel, Germany ; 3 Augsburg University, Germany

Keyword(s): Robustness, Organic Computing, Multi-agent-systems, Self-organisation.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Autonomous Systems ; Bioinformatics ; Biomedical Engineering ; Distributed and Mobile Software Systems ; Enterprise Information Systems ; Information Systems Analysis and Specification ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Methodologies and Technologies ; Multi-Agent Systems ; Operational Research ; Self Organizing Systems ; Simulation ; Software Engineering ; Symbolic Systems

Abstract: Organic Computing (OC) and Autonomic Computing (AC) systems are distinct from conventional systems through their ability to self-adapt and to self-organise. However, these properties are just means and not the end. What really makes OC and AC systems useful is their ability to survive in a real world, i.e. to recover from disturbances and attacks from the outside world. This property is called robustness. In this paper, we propose a metric to gauge robustness in order to be able to quantitatively compare the effectiveness of different self-organising and self-adaptive system designs with each other. In the following, we apply this metric to three experimental application scenarios and discuss their usefulness.

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Paper citation in several formats:
Kantert, J. ; Tomforde, S. ; Müller-Schloer, C. ; Edenhofer, S. and Sick, B. (2017). Quantitative Robustness – A Generalised Approach to Compare the Impact of Disturbances in Self-organising Systems. In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-219-6; ISSN 2184-433X, SciTePress, pages 39-50. DOI: 10.5220/0006137300390050

@conference{icaart17,
author={Jan Kantert and Sven Tomforde and Christian Müller{-}Schloer and Sarah Edenhofer and Bernard Sick},
title={Quantitative Robustness – A Generalised Approach to Compare the Impact of Disturbances in Self-organising Systems},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2017},
pages={39-50},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006137300390050},
isbn={978-989-758-219-6},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Quantitative Robustness – A Generalised Approach to Compare the Impact of Disturbances in Self-organising Systems
SN - 978-989-758-219-6
IS - 2184-433X
AU - Kantert, J.
AU - Tomforde, S.
AU - Müller-Schloer, C.
AU - Edenhofer, S.
AU - Sick, B.
PY - 2017
SP - 39
EP - 50
DO - 10.5220/0006137300390050
PB - SciTePress