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.