A multi-level grammar approach to grammar-guided genetic programming: the case of scheduling in heterogeneous networks

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Saber:GPEM,

• author = "Takfarinas Saber and David Fagan and David Lynch and Stepan Kucera and Holger Claussen and Michael O'Neill",
• title = "A multi-level grammar approach to grammar-guided genetic programming: the case of scheduling in heterogeneous networks",
• journal = "Genetic Programming and Evolvable Machines",
• year = "2019",
• volume = "20",
• number = "2",
• pages = "245--283",
• month = jun,
• keywords = "genetic algorithms, genetic programming, Telecommunication, Heterogeneous network, Scheduling, Grammar-guided genetic programming, Multi-level grammar, Seeding",
• ISSN = "1389-2576",
• DOI = "doi:10.1007/s10710-019-09346-4",
• size = "39 pages",
• abstract = "The scale at which the human race consumes data has increased exponentially in recent years. One key part in this increase has been the usage of smart phones and connected devices by the populous. Multi-level heterogeneous networks are the driving force behind this mobile revolution, but these are constrained with limited bandwidth and over-subscription. Scheduling users on these networks has become a growing issue. In recent years grammar-guided genetic programming (G3P) has shown its capability to evolve beyond human-competitive network schedulers. Despite the performance of the G3P schedulers, a large margin of improvement is demonstrated to still exist. In the pursuit of this goal we recently proposed a multi-level grammar approach to generating schedulers. The complexity of the grammar was increased at various stages during evolution, allowing for individuals to add more complex functions through variation operations. The goal is to evolve good quality solutions before allowing ...",

}

Genetic Programming entries for Takfarinas Saber David Fagan David Lynch Stepan Kucera Holger Claussen Michael O'Neill

Citations