Towards the Evolution of Multi-layered Neural Networks: A Dynamic Structured Grammatical Evolution Approach

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Assuncao:2017:GECCO,

• author = "Filipe Assuncao and Nuno Lourenco and Penousal Machado and Bernardete Ribeiro",
• title = "Towards the Evolution of Multi-layered Neural Networks: A Dynamic Structured Grammatical Evolution Approach",
• booktitle = "Proceedings of the Genetic and Evolutionary Computation Conference",
• series = "GECCO '17",
• year = "2017",
• isbn13 = "978-1-4503-4920-8",
• address = "Berlin, Germany",
• pages = "393--400",
• size = "8 pages",
• URL = "http://doi.acm.org/10.1145/3071178.3071286",
• DOI = "doi:10.1145/3071178.3071286",
• acmid = "3071286",
• publisher = "ACM",
• publisher_address = "New York, NY, USA",
• keywords = "genetic algorithms, genetic programming, grammatical evolution, Artificial Neural Networks, Classification, Grammar-based Genetic Programming, NeuroEvolution",
• month = "15-19 " # jul,
• abstract = "Current grammar-based NeuroEvolution approaches have several shortcomings. On the one hand, they do not allow the generation of Artificial Neural Networks (ANNs) composed of more than one hidden-layer. On the other, there is no way to evolve networks with more than one output neuron. To properly evolve ANNs with more than one hidden-layer and multiple output nodes there is the need to know the number of neurons available in previous layers. In this paper we introduce Dynamic Structured Grammatical Evolution (DSGE): a new genotypic representation that overcomes the aforementioned limitations. By enabling the creation of dynamic rules that specify the connection possibilities of each neuron, the methodology enables the evolution of multi-layered ANNs with more than one output neuron. Results in different classification problems show that DSGE evolves effective single and multi-layered ANNs, with a varying number of output neurons.",
• notes = "Also known as \cite{Assun\&\#xE7;\&\#xE3;o:2017:TEM:3071178.3071286} GECCO-2017 A Recombination of the 26th International Conference on Genetic Algorithms (ICGA-2017) and the 22nd Annual Genetic Programming Conference (GP-2017)",

}

Genetic Programming entries for Filipe Assuncao Nuno Lourenco Penousal Machado Bernardete Ribeiro

Citations