Solving the even-n-parity problems using Best SubTree Genetic Programming

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

@InProceedings{DBLP:conf/ahs/MunteanDO07,

• author = "Oana Muntean and Laura Diosan and Mihai Oltean",
• title = "Solving the even-n-parity problems using Best SubTree Genetic Programming",
• booktitle = "Second NASA/ESA Conference on Adaptive Hardware and Systems (AHS 2007)",
• year = "2007",
• bibsource = "DBLP, http://dblp.uni-trier.de",
• pages = "511--518",
• address = "Edinburgh",
• month = aug # " 5-8",
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming, digital circuits, logic design, trees (mathematics), digital circuit design, even-n-parity problem, subtree genetic programming",
• isbn13 = "0-7695-2866-X",
• DOI = "doi:10.1109/AHS.2007.99",
• size = "8 pages",
• abstract = "Best subtree genetic programming (BSTGP) is a special genetic programming (GP) variant whose aim is to offer more possibilities, for selecting the solution, compared to standard GP. In the case of BSTGP the best subtree is chosen for proving the solution. This is different from standard GP where the solution was given by the entire tree. In this paper we apply BSTGP for designing digital circuits for the even-n-parity problem. Numerical results show that BSTGP can improve GP search in terms of success rate and computational effort.",
• notes = "also https://mihaioltean.github.io/best_gp_digital_circuits.pdf",

}

Genetic Programming entries for Oana Muntean Laura Diosan Mihai Oltean

Citations