2013 IEEE 7th International Conference on Self-Adaptation and Self-Organizing Systems Workshops 2013
DOI: 10.1109/sasow.2013.17
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Designing Self-Aware Adaptive Systems: From Autonomic Computing to Cognitive Immune Networks

Abstract: Abstract-An autonomic system is composed of ensembles of heterogeneous autonomic components in which large sets of components are dynamically added and removed. Nodes within such an ensemble should cooperate to achieve system or human goals, and systems are expected to self-adapt with little or no human-interaction. Designing such systems poses significant challenges. In this paper we propose that the system engineer might gain significant inspiration by looking to the biological immune system, particularly by… Show more

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Cited by 9 publications
(3 citation statements)
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“…This work was more recently extended by Whitbrook et al (2010), in which the authors detailed how similar algorithms can be properly transferred in real robots. In Capodieci et al (2013a), the authors proposed that ideas from autonomic computing could be combined with immune-inspiration to provided distributed control. An idiotypic network algorithm was proposed and applied to selecting movement strategies in swarm foraging task in Capodieci et al (2013b).…”
Section: Related Workmentioning
confidence: 99%
“…This work was more recently extended by Whitbrook et al (2010), in which the authors detailed how similar algorithms can be properly transferred in real robots. In Capodieci et al (2013a), the authors proposed that ideas from autonomic computing could be combined with immune-inspiration to provided distributed control. An idiotypic network algorithm was proposed and applied to selecting movement strategies in swarm foraging task in Capodieci et al (2013b).…”
Section: Related Workmentioning
confidence: 99%
“…According to a fitness function that takes into account only local information, the concentration that characterizes each antibody inside each swarm individual changes over time so to provide the fittest immunological response in terms of kinetic parameters to be assigned to the swarm individual. The dynamics of this adaptive process follows a design methodology that we have previously formulated [12], [13] and applied in a robotic swarm foraging scenario [14]. We will show how this immune-inspired approach achieves self-organisation within the swarm, resulting in the creation of new shapes and behaviours, starting from a restricted set of recipes previously found with the hyperinteractive method.…”
Section: Related Workmentioning
confidence: 99%
“…Methods have been proposed to adapt autonomic components using evolutionary computing (EC) techniques as a response to environmental changes, e.g. [5,4]. These components exhibit cognition, namely learning and decisionmaking abilities, leading to collective self-awareness.…”
Section: Introductionmentioning
confidence: 99%