Symbolic Regression of Boolean Functions by Genetic Programming

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

@InCollection{Pospichal:2013:HBO,

• title = "Symbolic Regression of Boolean Functions by Genetic Programming",
• author = "Jiri Pospichal and Lubomir Varga and Vladimir Kvasnicka",
• booktitle = "Handbook of Optimization",
• publisher = "Springer",
• year = "2013",
• editor = "Ivan Zelinka and Vaclav Snasel and Ajith Abraham",
• volume = "38",
• series = "Intelligent Systems Reference Library",
• pages = "263--286",
• address = "Berlin",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-642-30503-0",
• DOI = "doi:10.1007/978-3-642-30504-7_11",
• abstract = "An evolutionary metaphor of genetic programming for a symbolic regression of Boolean functions, which represent logic circuits, is studied. These functions are coded by acyclic oriented graphs with vertices corresponding to elementary Boolean operations, e. g. negation, conjunction, disjunction (both inclusive and exclusive), and their negations. The used acyclic oriented graphs are represented by the so-called column tables. Basic genetic operations of mutation and crossover are performed over these column tables. Preliminary results indicate that the proposed version of genetic programming with column tables is an effective evolutionary tool for a construction of optimised Boolean functions that are specified by tables of functional values for all possible combinations of arguments.",
• notes = "Institute of Applied Informatics at FIIT, Slovak Technical University, 842 16, Bratislava, Slovakia",

}

Genetic Programming entries for Jiri Pospichal Lubomir Varga Vladimir Kvasnicka

Citations