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GRAPE: Grammatical algorithms in python for evolution

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journal contribution
posted on 2023-03-16, 16:21 authored by Allan de LimaAllan de Lima, Samuel Carvalho, Douglas Mota DiasDouglas Mota Dias, ENRIQUE NAREDOENRIQUE NAREDO, Joseph P. Sullivan, Conor RyanConor Ryan

GRAPE is an implementation of Grammatical Evolution (GE) in DEAP, an Evolutionary Computation framework in Python, which consists of the necessary classes and functions to evolve a population of grammar-based solutions, while reporting essential measures. This tool was developed at the Bio-computing and Developmental Systems (BDS) Research Group, the birthplace of GE, as an easy to use (compared to the canonical C++ implementation, libGE) tool that inherits all the advantages of DEAP, such as selection methods, parallelism and multiple search techniques, all of which can be used with GRAPE. In this paper, we address some problems to exemplify the use of GRAPE and to perform a comparison with PonyGE2, an existing implementation of GE in Python. The results show that GRAPE has a similar performance, but is able to avail of all the extra facilities and functionality found in the DEAP framework. We further show that GRAPE enables GE to be applied to systems identification problems and we demonstrate this on two benchmark problems.


Automatic Design of Digital Circuits (ADDC)

Science Foundation Ireland

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Signals, 3 pp. 642-663



Other Funding information

This publication has emanated from research conducted with the financial support of Science Foundation Ireland under Grant number 16/IA/4605. The third author is also financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brazil (CAPES), Finance Code 001, and the Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ). Open Access funding provided by the IRel Consortium

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