Geometric Differential Evolution for Combinatorial and Programs Spaces

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Moraglio:2013:EC,

• author = "A. Moraglio and J. Togelius and S. Silva",
• title = "Geometric Differential Evolution for Combinatorial and Programs Spaces",
• journal = "Evolutionary Computation",
• year = "2013",
• volume = "21",
• number = "4",
• pages = "591--624",
• month = "Winter",
• keywords = "genetic algorithms, genetic programming, DE, NK, TSP, Sudoku, Differential evolution, representations, principled design of search operators, combinatorial spaces, theory",
• ISSN = "1063-6560",
• URL = "https://ore.exeter.ac.uk/repository/bitstream/handle/10871/13627/Geometric%20differential%20evolution%20for%20combinatorial%20and%20programs%20spaces.pdf",
• URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.298.3320",
• DOI = "doi:10.1162/EVCO_a_00099",
• size = "34 pages",
• abstract = "Geometric differential evolution (GDE) is a recently introduced formal generalisation of traditional differential evolution (DE) that can be used to derive specific differential evolution algorithms for both continuous and combinatorial spaces retaining the same geometric interpretation of the dynamics of the DE search across representations. In this article, we first review the theory behind the GDE algorithm, then, we use this framework to formally derive specific GDE for search spaces associated with binary strings, permutations, vectors of permutations and genetic programs. The resulting algorithms are representation-specific differential evolution algorithms searching the target spaces by acting directly on their underlying representations. We present experimental results for each of the new algorithms on a number of well-known problems comprising NK-landscapes, TSP, and Sudoku, for binary strings, permutations and vectors of permutations. We also present results for the Regression, Artificial Ant, Parity and Multiplexer problems within the genetic programming domain. Experiments show that overall the new DE algorithms are competitive with well-tuned standard search algorithms.",
• notes = "Posted online on 27 Dec 2012. oai:CiteSeerX.psu:10.1.1.298.3320 is draft?",

}

Genetic Programming entries for Alberto Moraglio Julian Togelius Sara Silva

Citations