An Examination of Synchronisation in Artificial Gene Regulatory Networks

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@InProceedings{byrne:aeosiagrn:cec2014,

• title = "An Examination of Synchronisation in Artificial Gene Regulatory Networks",
• author = "Jonathan Byrne and Miguel Nicolau and Anthony Brabazon and Michael O'Neill",
• pages = "2764--2769",
• booktitle = "Proceedings of the 2014 IEEE Congress on Evolutionary Computation",
• year = "2014",
• month = "6-11 " # jul,
• editor = "Carlos A. {Coello Coello}",
• address = "Beijing, China",
• publisher = "IEEE Press",
• ISBN = "0-7803-8515-2",
• keywords = "genetic algorithms, genetic programming, Evolutionary Developmental Systems, Complex Networks and Evolutionary Computation",
• DOI = "doi:10.1109/CEC.2014.6900385",
• abstract = "An Artificial Genetic Regulatory Network (GRN) is a model of the gene expression regulation mechanism in biological organisms. It is a dynamical system that is capable of mimicking non-linear time series. The GRN was adapted to allow for input and output so that the system's rich dynamics could be used for dynamic problem solving. In order for the GRN to be embedded in the environment, the time scale of the physical system has to be mapped to that of the GRN and so a synchronisation process was introduced. This work examines the impact of different synchronisation intervals and how they effect the overall performance of the GRN. A variable synchronisation step that stops once the system has stabilised is also explored as a mechanism for automatically choosing the interval size.",
• notes = "Also known as \cite{Byrne:2014:CEC}",

}

Genetic Programming entries for Jonathan Byrne Miguel Nicolau Anthony Brabazon Michael O'Neill

Citations