- author = "Naoyuki Kubota and Fumio Kojima and Setsuo Hashimoto and Toshio Fukuda",
- title = "Information transformation by virus-evolutionary genetic programming",
- journal = "Artificial Life and Robotics",
- year = "2000",
- volume = "4",
- number = "3",
- pages = "171--174",
- month = sep,
- keywords = "genetic algorithms, genetic programming, Computational intelligence, Classifier system",
- ISSN = "1433-5298",
-
DOI = "
doi:10.1007/BF02481340",
- abstract = "This paper deals with genetic programming (GP) for information translation. The GP can generate a structured computer program, but it is difficult to define recursive functions automatically. Therefore, we propose a virus-evolutionary genetic programming (VE-GP) composed of two populations; host and virus. Here, a virus plays the role of an automatically defined function. First, the VE-GP is applied to a function approximation problem, and the simulation result shows that the VE-GP can generate a function to approximate the given function with small errors. Next, the VE-GP is applied to the information transformation for a classification task, and the simulation result shows that the VE-GP can generate a function to classify a given data set.",
-
notes = "This work was presented in part at the Fourth
International Symposium on Artificial Life and
Robotics, Oita, Japan, January 19-22, 1999
\cite{kubota:1999:itveGP}
(1) Department of Human and Artificial Intelligent Systems, Fukui University, 3-9-1 Bunkyo, 910-8507 Fukui, Japan (2) Graduate School of Science and Technology, Division of System Function Science, Kobe University, Kobe, Japan (3) Center for Cooperative Research in Advanced Science and Technology, Nogoya University, Nagoya, Japan",
