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Evolving Parameters for a Noisy Biological System – The Impact of Alternative Approaches

Barnes, David J., Chu, Dominique (2014) Evolving Parameters for a Noisy Biological System – The Impact of Alternative Approaches. In: Artificial Intelligence and Soft Computing: Part II. Lecture Notes in Computer Science , 8468. pp. 95-106. Springer International Publishing ISBN 978-3-319-07175-6. E-ISBN 978-3-319-07176-3. (doi:10.1007/978-3-319-07176-3_9) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided)

Abstract

In this contribution we seek to evolve viable parameter values for a small-scale biological network motif concerned with bacterial nutrient uptake and metabolism. We use two different evolutionary approaches with the model: implicit and explicit. Our results reveal that significantly different characteristics of both efficiency and timescale emerge in the resulting evolved systems depending on the which particular approach is used.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1007/978-3-319-07176-3_9
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Sciences > School of Computing > Computational Intelligence Group
Depositing User: Dominique Chu
Date Deposited: 24 Jun 2014 09:43 UTC
Last Modified: 29 May 2019 12:42 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/41515 (The current URI for this page, for reference purposes)
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