Authors:
Sven Tomforde
1
;
Jan Kantert
2
and
Bernard Sick
1
Affiliations:
1
University of Kassel, Germany
;
2
Leibniz Universität Hannover, Germany
Keyword(s):
Self-organisation, Quantification of Self-organisation, Organic Computing, Adaptivity, Probabilistic Models, Communication Patterns.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Self Organizing Systems
Abstract:
The term “self-organisation” typically refers to the ability of large-scale systems consisting of numerous autonomous
agents to establish and maintain their structure as a result of local interaction processes. The motivation
to develop systems based on the principle of self-organisation is to counter complexity and to improve
desired characteristics, such as robustness and context-adaptivity. In order to come up with a fair comparison
between different possible solutions, a prerequisite is that the degree of self-organisation is quantifiable. Even
though there are some attempts in literature that try to approach such a measure, there is none that is real-world
applicable, covers the entire runtime process of a system, and considers agents as blackboxes (i.e. does not
require internals about status or strategies). With this paper, we introduce a concept for such a metric that
is based on external observations, neglects the internal behaviour and strategies of autonomous entities, and
provides a continuous measure that allows for an easy comparibility.
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