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Grammatical evolution is an evolutionary algorithm able to develop programs in any language, defined by a grammar. The evolutionary process may be improved if we let the individuals learn during their lifetime. with this aim, the grammatical evolution guided by reinforcement, an algorithm which merges evolution and learning, was created. Grammatical evolution guided by reinforcement uses a Lamarckian mechanism for replacing the original genotypes when a successful learning has occurred. This paper explores the role of the Lamarckian hypothesis. At the same time, grammatical evolution guided by reinforcement is tested in a new domain: autonomous navigation in a Kephera robot simulation.