Abstract
The EvoEvo project was a 2013–2017 FP7 European project aiming at developing new evolutionary approaches in information science and producing novel algorithms based on the current understanding of molecular and evolutionary biology, with the ultimate goals of addressing open-ended problems in which the specifications are either unknown or too complicated to express, and of producing software able to operate even in unpredictable, varying conditions. Here we present the main rationals of the EvoEvo project and propose a set of design rules to evolve adaptive software systems.
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Notes
- 1.
The following text is massively derived from the EvoEvo project documents. In particular, many paragraphs are derived from the EvoEvo Description of Work (DoW) and from the project Final Report (EvoEvo Deliverable 6.8), available at www.evoevo.eu.
- 2.
ICT-2013.9.6 – FET Proactive: Evolving Living Technologies (EVLIT).
- 3.
Clustering is a data-mining task that aims to group objects sharing similar characteristics into a same cluster over the whole data space. Subspace clustering similarly aims at identifying groups of similar objects, but it also aims at detecting the subspaces where similarity occurs. Hence it can be conceived as “similarity examined under different representations” [23]. Subspace clustering is recognized as a more complicated and general task than standard clustering. Moreover, retrieving meaningful subspaces is particularly useful when dealing with high dimensional data [21].
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Acknowledgments
This work was supported by the European Commission \(7^{th}\) Framework Program (FP7-ICT-2013.9.6 FET Proactive: Evolving Living Technologies) EvoEvo project (ICT- 610427, http://www.evovo.eu/). The authors thank all the partners of the EvoEvo project for fruitful discussions.
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Beslon, G., Elena, S.F., Hogeweg, P., Schneider, D., Stepney, S. (2018). Evolving Living Technologies—Insights from the EvoEvo Project. In: Colanzi, T., McMinn, P. (eds) Search-Based Software Engineering. SSBSE 2018. Lecture Notes in Computer Science(), vol 11036. Springer, Cham. https://doi.org/10.1007/978-3-319-99241-9_2
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