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GECCO
2005
Springer

Evolving recurrent models using linear GP

9 years 5 months ago
Evolving recurrent models using linear GP
Turing complete Genetic Programming (GP) models introduce the concept of internal state, and therefore have the capacity for identifying interesting temporal properties. Surprisingly, there is little evidence of the application of such models to problems for prediction. An empirical evaluation is made of a simple recurrent linear GP model over standard prediction problems. Categories and Subject Descriptors I.2.6 [Computing Methodologies]: Learning – Parameter Learning. General Terms Algorithms, Experimentation, Languages. Keywords Recurrent Architectures, Linear Genetic Programming.
Xiao Luo, Malcolm I. Heywood, A. Nur Zincir-Heywoo
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where GECCO
Authors Xiao Luo, Malcolm I. Heywood, A. Nur Zincir-Heywood
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