Efficient Evolution of Asymetric Recurrent Neural Networks Using a PDGP-inspired Two-dimensional Representation

Created by W.Langdon from gp-bibliography.bib Revision:1.7954

@InProceedings{pujol:1998:eearNN,

• author = "Joao Carlos Figueira Pujol and Riccardo Poli",
• title = "Efficient Evolution of Asymetric Recurrent Neural Networks Using a PDGP-inspired Two-dimensional Representation",
• booktitle = "Proceedings of the First European Workshop on Genetic Programming",
• year = "1998",
• editor = "Wolfgang Banzhaf and Riccardo Poli and Marc Schoenauer and Terence C. Fogarty",
• volume = "1391",
• series = "LNCS",
• pages = "130--141",
• address = "Paris",
• publisher_address = "Berlin",
• month = "14-15 " # apr,
• publisher = "Springer-Verlag",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "3-540-64360-5",
• URL = "http://cswww.essex.ac.uk/staff/poli/papers/Pujol-EUROGP1998.pdf",
• URL = "http://citeseer.ist.psu.edu/305558.html",
• DOI = "doi:10.1007/BFb0055933",
• abstract = "Recurrent neural networks are particularly useful for processing time sequences and simulating dynamical systems. However, methods for building recurrent architectures have been hindered by the fact that available training algorithms are considerably more complex than those for feedforward networks. In this paper, we present a new method to build recurrent neural networks based on evolutionary computation, which combines a linear chromosome with a two-dimensional representation inspired by Parallel Distributed Genetic Programming (a form of genetic programming for the evolution of graph-like programs) to evolve the architecture and the weights simultaneously. Our method can evolve general asymmetric recurrent architectures as well as specialized recurrent architectures. This paper describes the method and reports on results of its application.",
• notes = "EuroGP'98. Artificial Ant John Muir Trail",
• affiliation = "The University of Birmingham School of Computer Science B15 2TT Birmingham UK B15 2TT Birmingham UK",

}

Genetic Programming entries for Joao Carlos Figueira Pujol Riccardo Poli

Citations