@inbook{4ee60fc6d7a64d90ae8500e3ae69455f,
title = "Comparing the robustness of grammatical genetic programming solutions for femtocell algorithms",
abstract = "We compare how multiple of training scenarios in the evolutionary search produce different solutions and performance on training and test scenarios. The experiments use grammar based Genetic Programming on the Femtocell problem with one grammar for generating real-values and another grammar for generating discrete values for changing the pilot power. The use of a grammar which produces discrete changes to the pilot power generate better solutions on the training and the test scenarios. Copyright is held by the author/owner(s).",
keywords = "Femtocell, Grammatical evolution, Symbolic regression",
author = "Erik Hemberg and Lester Ho and Michael O'Neill and Holger Claussen",
year = "2012",
doi = "10.1145/2330784.2331028",
language = "English",
isbn = "9781450311786",
series = "GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion",
publisher = "Association for Computing Machinery ",
pages = "1525--1526",
booktitle = "GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion",
address = "United States",
note = "14th International Conference on Genetic and Evolutionary Computation Companion, GECCO'12 Companion ; Conference date: 07-07-2012 Through 11-07-2012",
}