Abstract
A novel algorithm uses standard Genetic Programming (GP) to evolve an Attribute Grammar (AG) and this is tested on a problem with known solution in automatic code parallelization. Standard GP first generates a vector of real numbers and its elements are in turn applied to the grammar. As the parse tree is being produced the choices in the grammar depend on the attributes being input to the current node of the parse tree. Experiments reveal different levels of success at finding solutions to different versions of the test problem. It is speculated that the novel method may find a role in computational medicine in stem cell research and in the modelling of epigenetic disease.
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Howard, D., Ryan, C., Collins, J.J.: Attribute Grammar Genetic Programming Algorithm for Automatic Code Parallelization. In: Lee, G., Howard, D., Ślęzak, D. (eds.) ICHIT 2011. LNCS, vol. 6935, pp. 250–257. Springer, Heidelberg (2011) ISBN 978-3-642-24081-2
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© 2012 Springer-Verlag Berlin Heidelberg
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Howard, D., Ryan, C. (2012). Testing a Novel Attribute Grammar Genetic Programming Algorithm. In: Lee, G., Howard, D., Kang, J.J., Ślęzak, D. (eds) Convergence and Hybrid Information Technology. ICHIT 2012. Lecture Notes in Computer Science, vol 7425. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32645-5_29
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DOI: https://doi.org/10.1007/978-3-642-32645-5_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32644-8
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