The influence of learning on evolution
Adaptive individuals in evolving populations
Adding learning to the cellular development of neural networks: Evolution and the baldwin effect
Evolutionary Computation
Cultural transmission of information in genetic programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
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We consider a form of phenotype plasticity in Genetic Programming (GP). This takes the form of a set of real-valued numerical parameters associated with each individual, an optimisation (or learning) algorithm for adapting their values, and an inheritance strategy for propagating learned parameter values to offspring. We show that plastic GP has significant benefits including faster evolution and adaptation in changing environments compared with non-plastic GP. The paper also considers the differences between Darwinian and Lamarckian inheritance schemes and shows that the former is superior in dynamic environments.