how is grammatic evolution different from grammar-based genetic programming?

There are two closely related techniques in genetic programming. One of them is grammar based genetic programming (GBGP), which uses context free grammar to generate a derivative tree which represents the program.

The other is grammatical evolution which uses something called genomes and codons, which is then mapped to a phenotype, a realization.

The part where I get confused is, the phenotype realization can also be represented as a derivative tree. The codon to rule mapping is done through a modulo operator which seem to be a random sampling to me as well.

So how is it different from the usual GBGP?

Topic grammar-inference genetic-programming ai genetic-algorithms machine-learning

Category Data Science

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