Prudent alignment and crossover of decision trees in genetic programming

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

@Article{Sprogar:2015:GPEM,

• author = "Matej Sprogar",
• title = "Prudent alignment and crossover of decision trees in genetic programming",
• journal = "Genetic Programming and Evolvable Machines",
• year = "2015",
• volume = "16",
• number = "4",
• pages = "499--530",
• month = dec,
• keywords = "genetic algorithms, genetic programming, Decision trees, Crossover, Context, Alignment",
• ISSN = "1389-2576",
• DOI = "doi:10.1007/s10710-015-9243-7",
• size = "32 pages",
• abstract = "Crossover is the central search operator responsible for navigating through unknown problem landscapes while at the same time the main conservation operator, which is supposed to preserve the already learnt lessons. This paper is about a novel homologous decision tree crossover operator. Contrary to other tree crossover operators it defines the context for a decision tree node and elaborates a fast one-sample-based tree alignment procedure. The idea is to replace a sub-tree with a better one from the same context, as defined by the decision tree training process. This operator does not rely on the topological properties of the tree but rather on its behavioural properties. During empirical testing the new operator showed the best generalisation capabilities.",

}

Genetic Programming entries for Matej Sprogar

Citations