Evolutionary Computation Meets Stream Processing

Created by W.Langdon from gp-bibliography.bib Revision:1.7650

@InProceedings{Gulisano:2024:evoapplications,

• author = "Vincenzo Gulisano and Eric Medvet",
• title = "Evolutionary Computation Meets Stream Processing",
• booktitle = "27th International Conference, EvoApplications 2024",
• year = "2024",
• editor = "Stephen Smith and Joao Correia and Christian Cintrano",
• series = "LNCS",
• volume = "14634",
• publisher = "Springer",
• address = "Aberystwyth",
• month = "3-5 " # apr,
• pages = "377--393",
• organisation = "EvoStar, Species",
• keywords = "genetic algorithms, genetic programming, Parallellization, Design of EAs, Distributed computing, symbolic regressio",
• isbn13 = "978-3-031-56851-0",
• URL = "https://rdcu.be/dDZXz",
• DOI = "doi:10.1007/978-3-031-56852-7_24",
• abstract = "Evolutionary computation (EC) has a great potential of exploiting parallelisation, a feature often under emphasised when describing evolutionary algorithms (EAs). we show that the paradigm of stream processing (SP) can be used to express EAs in a way that allows the immediate exploitation of parallel and distributed computing, not at the expense of the agnosticity of the EAs with respect to the application domain. We introduce the first formal framework for EC based on SP and describe several building blocks tailored to EC. Then, we experimentally validate our framework and show that (a) it can be used to express common EAs, (b) it scales when deployed on real-world stream processing engines (SPEs), and (c) it facilitates the design of EA modifications which would require a larger effort with traditional implementation.",
• notes = "http://www.evostar.org/2024/ EvoApplications2024 held in conjunction with EuroGP'2024, EvoCOP2024 and EvoMusArt2024",

}

Genetic Programming entries for Vincenzo Gulisano Eric Medvet

Citations