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Differential Gene Expression with Tree-Adjunct Grammars
Eoin Murphy, Miguel Nicolau, Erik Hemberg, Michael O’Neill, and Anthony Brabazon
Natural Computing Research and Applications Group, Univeristy College Dublin, Irelandeoin.murphy@ucd.ie
miguel.nicolau@ucd.ie
erik.hemberg@ucd.ie
m.oneill@ucd.ie
anthony.brabazon@ucd.ie
Abstract. A novel extension of an existing artificial Gene Regulatory Network model is introduced, combining the dynamic adaptive nature of this model with the generative power of grammars. The use of grammars enables the model to produce more varied phenotypes, allowing its application to a wider range of problems. The performance and generalisation ability of the model on the inverted-pendulum problem, using a range of different grammars, is compared against the existing model.
LNCS 7491, p. 377 ff.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2012