Committees as artificial organisms – Evolution and adaptation

Roberto C. Alamino*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Generalised committee machines are here proposed to model the interaction of the DNA of a simplified artificial organism with its environment and shown to induce a unique genotype-phenotype map. An application to organisms being subjected to a toxic environment is shown to allow for a generalised form of antagonistic pleiotropy. The same scenario is studied in order to show the difference in adaptation in the presence of a fitness cost given by a lower reproduction rate.

Original languageEnglish
Title of host publicationESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
Pages31-36
Number of pages6
ISBN (Electronic)9782875870650
Publication statusPublished - 26 Apr 2019
Event27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2019 - Bruges, Belgium
Duration: 24 Apr 201926 Apr 2019

Conference

Conference27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2019
CountryBelgium
CityBruges
Period24/04/1926/04/19

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    Alamino, R. C. (2019). Committees as artificial organisms – Evolution and adaptation. In ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (pp. 31-36)