Abstract
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.
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