This paper introduces Structured Grammatical Evolution, a new genotypic representation for Grammatical Evolution, where each gene is explicitly linked to a non-terminal of the grammar being used. This one-to-one correspondence ensures that the modification of a gene does not affect the derivation options of other non-terminals, thereby increasing locality. The performance of the new representation is accessed on a set of benchmark problems. The results obtained confirm the effectiveness of the proposed approach, as it is able to outperform standard grammatical evolution on all selected optimisation problems.
Conference
Artificial Evolution 2015, October 2015
PDF File
Cited by
Year 2018 : 7 citations
Medvet, E., Bartoli, A., De Lorenzo, A., & Tarlao, F. (2018). Designing automatically a representation for grammatical evolution. Genetic Programming and Evolvable Machines, 1-29.
Medvet, E., Bartoli, A., De Lorenzo, A., & Tarlao, F. (2018, September). GOMGE: Gene-Pool Optimal Mixing on Grammatical Evolution. In International Conference on Parallel Problem Solving from Nature (pp. 223-235). Springer, Cham.
Bartoli, A., Castelli, M., & Medvet, E. (2018). Weighted Hierarchical Grammatical Evolution. IEEE Transactions on Cybernetics.
Ryan, C., O’Neill, M., & Collins, J. J. (2018). Introduction to 20 Years of Grammatical Evolution. In Handbook of Grammatical Evolution (pp. 1-21). Springer, Cham.
Medvet, E., & Bartoli, A. (2018, April). On the Automatic Design of a Representation for Grammar-Based Genetic Programming. In European Conference on Genetic Programming (pp. 101-117). Springer, Cham.
Fagan, D., & Murphy, E. (2018). Mapping in Grammatical Evolution. In Handbook of Grammatical Evolution (pp. 79-108). Springer, Cham.
Medvet, E., Virgolin, M., Castelli, M., Bosman, P. A., Gonçalves, I., & Tušar, T. (2018). Unveiling evolutionary algorithm representation with DU maps. Genetic Programming and Evolvable Machines, 19(3), 351-389.
Year 2017 : 6 citations
Medvet, E. (2017). Hierarchical Grammatical Evolution. In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO.
Medvet, E., Daolio, F., and Tagliapietra, D. (2017). Evolvability in Grammatical Evolu- tion. In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO.
Medvet, E., and Tušar, T. (2017). The DU Map: A Visualization to Gain Insights into Genotype-Phenotype Mapping and Diversity.
Ryser-Welch, P. (2017). Evolving comprehensible and scalable solvers using CGP for solving some real-world inspired problems (Doctoral dissertation, University of York).
Medvet, Eric, Alberto Bartoli, and Jacopo Talamini. "Road Traffic Rules Synthesis using Grammatical Evolution."
Medvet, Eric. "A Comparative Analysis of Dynamic Locality and Redundancy in Grammatical Evolution."
