@inproceedings{7aa2a7f474954d1285b91838b03d7edd,
title = "Testing a novel attribute grammar genetic programming algorithm",
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.",
keywords = "Attribute Grammar, Automatic Parallelization, Evolutionary Computation, Genetic Programming, Grammatical Evolution, Parallel Computing, algorithm, epigenetic diseases, stem cells",
author = "Daniel Howard and Conor Ryan",
year = "2012",
doi = "10.1007/978-3-642-32645-5_29",
language = "English",
isbn = "9783642326448",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "224--231",
booktitle = "Convergence and Hybrid Information Technology - 6th International Conference, ICHIT 2012, Proceedings",
note = "6th International Conference on Convergence and Hybrid Information Technology, ICHIT 2012 ; Conference date: 23-08-2012 Through 25-08-2012",
}