Genetic Programming Algorithm Creating and Assembling Subtrees for Making Analytical Functions

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Cadrik:2016:MENDEL,

• author = "Tomas Cadrik and Marian Mach",
• title = "Genetic Programming Algorithm Creating and Assembling Subtrees for Making Analytical Functions",
• booktitle = "Proceedings of the 22nd International Conference on Soft Computing (MENDEL 2016)",
• year = "2016",
• editor = "Radek Matousek",
• volume = "576",
• series = "AISC",
• pages = "55--63",
• address = "Brno, Czech Republic",
• month = jun # " 8-10",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-319-58087-6",
• ISSN = "2194-5357",
• DOI = "doi:10.1007/978-3-319-58088-3_6",
• abstract = "There are many optimization algorithms which can be used for solving different tasks. One of those is the genetic programming method, which can build an analytical function which can describe data. The function is coded in a tree structure. The problem is that when we decide to use lower maximal depth of the tree, the genetic programming is not able to compose a function which is good enough. This paper describes the way how to solve this problem. The approach is based on creating partial solutions represented by subtrees and composing them together to create the last tree. This approach was tested for finding a function which can correctly calculate the output according to the given inputs. The experiments showed that even when using a small maximal depth, the genetic programming using our approach can create functions with good results.",
• notes = "https://link.springer.com/book/10.1007/978-3-319-58088-3 ICSC-MENDEL 2016 Recent Advances in Soft Computing",

}

Genetic Programming entries for Tomas Cadrik Marian Mach

Citations