Evolving recurrent models using linear GP
Xiao Luo, Malcolm Iain Heywood, Nur Zincir-Heywood · 2005
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.