Researchers have been interested in exploring the regularities and modularity of the problem space in genetic programming (GP) with the aim of decomposing the original problem into several smaller subproblems. The main motivation is to allow GP to deal with more complex problems. Most previous works on modularity in GP emphasise the structure of modules used to encapsulate code and/or promote code reuse, instead of in the decomposition of the original problem. In this paper we propose a problem decomposition strategy that allows the use of a GP search to find solutions for subproblems and combine the individual solutions into the complete solution to the problem. © 2013 Springer-Verlag.
CITATION STYLE
Otero, F. E. B., & Johnson, C. G. (2013). Automated problem decomposition for the Boolean domain with genetic programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7831 LNCS, pp. 169–180). https://doi.org/10.1007/978-3-642-37207-0_15
Mendeley helps you to discover research relevant for your work.