Abstract
In the software domain, self-adaptive systems are able to modify their behavior at run-time to respond to changes in the environment they run, to changes of the users' requirements or to changes occurring in the system it-self. In life science, biological cells are power entities able to adapt to the (unpredictable) situations they incur in, in a complete decentralized fashion. Learning adaptation mechanism from the cell life-cycle, we propose in this paper a new architectural paradigm for self-adaptive software systems. © 2010 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Di Marco, A., Gallo, F., Inverardi, P., & Ippoliti, R. (2010). Learning from the cell life-cycle: A self-adaptive paradigm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6285 LNCS, pp. 485–488). https://doi.org/10.1007/978-3-642-15114-9_46
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