abstract = "This paper is concerned with the challenge of learning
solutions to problems. The method employed here is a
grammar based heuristic, where domain knowledge is
encoded in a generative grammar, while evolution drives
the update of the population of solutions. Furthermore
the method can adapt to the environment by altering the
grammar. The implementation consists of the
grammar-based Genetic Programming approach of
Grammatical Evolution (GE). A number of different
constructions of grammars and operators for
manipulating the grammars and the evolutionary
algorithm are investigated, as well as a meta-grammar
GE which allows a more flexible grammar. The results
show some benefit of using meta-grammars in GE and
re-emphasize the grammar's impact on GE's
performance.",