Barnes, David J. and Chu, Dominique (2014) Evolving Parameters for a Noisy Biological System – The Impact of Alternative Approaches. In: Artificial Intelligence and Soft Computing 13th International Conference. Lecture Notes in Computer Science, 2 . Springer, Cham, Switzerland, pp. 95-106. 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) (KAR id:41515)
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Official URL: http://dx.doi.org/10.1007/978-3-319-07176-3_9 |
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: | Book section |
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DOI/Identification number: | 10.1007/978-3-319-07176-3_9 |
Uncontrolled keywords: | genetic algorithm; network motif; genetic algorithm approach; implicit solution; implicit approach |
Subjects: |
Q Science > Q Science (General) > Q335 Artificial intelligence Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Dominique Chu |
Date Deposited: | 24 Jun 2014 09:43 UTC |
Last Modified: | 17 Aug 2022 10:57 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/41515 (The current URI for this page, for reference purposes) |
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