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Evolutionary acquisition of complex traits in artificial epigenetic networks

Turner, Alexander; Tyrrell, Andy; Trefzer, Martin; Lones, Michael


Alexander Turner

Andy Tyrrell

Martin Trefzer

Michael Lones


How complex traits arise within organisms over evolutionary time is an important question that has relevance both to the understanding of biological systems and to the design of bio-inspired computing systems. This paper investigates the process of acquiring complex traits within epiNet, a recurrent connectionist architecture capable of adapting its topology during execution. Inspired by the biological processes of gene regulation and epigenetics, epiNet captures biological organisms’ ability to alter their regulatory topologies according to environmental stimulus. By applying epiNet to a series of computational tasks, each requiring a range of complex behaviours to solve, and capturing the evolutionary process in detail, we can show not only how the physical structure of epiNet changed when acquiring complex traits, but also how these changes in physical structure affected its dynamic behaviour. This is facilitated by using a lightweight optimisation method which makes minor iterative changes to the network structure so that when complex traits emerge for the first time, a direct lineage can be observed detailing exactly how they evolved. From this we can build an understanding of how complex traits evolve and which regulatory environments best allow for the emergence of these complex traits, pointing us towards computational models that allow more swift and robust acquisition of complex traits when optimised in an evolutionary computing setting.


Turner, A., Tyrrell, A., Trefzer, M., & Lones, M. (2019). Evolutionary acquisition of complex traits in artificial epigenetic networks. BioSystems, 176, 17-26.

Journal Article Type Article
Acceptance Date Dec 4, 2018
Online Publication Date Dec 14, 2018
Publication Date 2019-02
Deposit Date Feb 13, 2019
Publicly Available Date Feb 13, 2019
Journal Biosystems
Print ISSN 0303-2647
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 176
Pages 17-26
Keywords General Biochemistry, Genetics and Molecular Biology; Modelling and Simulation; Statistics and Probability; Applied Mathematics; General Medicine
Public URL
Publisher URL
Additional Information This article is maintained by: Elsevier; Article Title: Evolutionary acquisition of complex traits in artificial epigenetic networks; Journal Title: Biosystems; CrossRef DOI link to publisher maintained version:; Content Type: article; Copyright: © 2018 The Authors. Published by Elsevier B.V.


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Copyright Statement
© 2018 The Authors.<br /> <br /> This work is licensed under a Creative Commons Attribution 4.0 International License.

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