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Presenting the ECO: Evolutionary Computation Ontology

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Applications of Evolutionary Computation (EvoApplications 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10199))

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Abstract

A well-established notion in Evolutionary Computation (EC) is the importance of the balance between exploration and exploitation. Data structures (e.g. for solution encoding), evolutionary operators, selection and fitness evaluation facilitate this balance. Furthermore, the ability of an Evolutionary Algorithm (EA) to provide efficient solutions typically depends on the specific type of problem. In order to obtain the most efficient search, it is often needed to incorporate any available knowledge (both at algorithmic and domain level) into the EA. In this work, we develop an ontology to formally represent knowledge in EAs. Our approach makes use of knowledge in the EC literature, and can be used for suggesting efficient strategies for solving problems by means of EC. We call our ontology “Evolutionary Computation Ontology” (ECO). In this contribution, we show one possible use of it, i.e. to establish a link between algorithm settings and problem types. We also show that the ECO can be used as an alternative to the available parameter selection methods and as a supporting tool for algorithmic design.

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Notes

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    Available online at: http://www.goo.gl/xSgVvv.

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Acknowledgments

figure b

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 665347.

Author information

Authors and Affiliations

  1. Department of Mathematics and Computer Science, Eindhoven University of Technology, P.O. Box 513, 5600 MB, Eindhoven, The Netherlands

    Anil Yaman

  2. INCAS3, P.O. Box 797, 9400 AT, Assen, The Netherlands

    Anil Yaman, Matt Coler & Giovanni Iacca

  3. Chair for Integrated Signal Processing Systems, RWTH Aachen University, 52056, Aachen, Germany

    Ahmed Hallawa

  4. Campus Fryslân, University of Groningen, Sophialaaan 1, 8911 AE, Leeuwarden, The Netherlands

    Matt Coler

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  1. Anil Yaman
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  2. Ahmed Hallawa
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  4. Giovanni Iacca
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Correspondence to Giovanni Iacca .

Editor information

Editors and Affiliations

  1. Politecnico di Torino, Turin, Italy

    Giovanni Squillero

  2. Edinburgh Napier University, Edinburgh, United Kingdom

    Kevin Sim

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Yaman, A., Hallawa, A., Coler, M., Iacca, G. (2017). Presenting the ECO: Evolutionary Computation Ontology. In: Squillero, G., Sim, K. (eds) Applications of Evolutionary Computation. EvoApplications 2017. Lecture Notes in Computer Science(), vol 10199. Springer, Cham. https://doi.org/10.1007/978-3-319-55849-3_39

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  • DOI: https://doi.org/10.1007/978-3-319-55849-3_39

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