A Knowledge-Evolution Strategy Based on Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Kuo:2008:ICHIT,

• author = "Chan-Sheng Kuo and Tzung-Pei Hong and Chuen-Lung Chen",
• title = "A Knowledge-Evolution Strategy Based on Genetic Programming",
• booktitle = "International Conference on Convergence and Hybrid Information Technology, ICHIT '08",
• year = "2008",
• month = aug,
• pages = "43--48",
• keywords = "genetic algorithms, genetic programming, evolutionary process, integrated classification tree, knowledge management, knowledge-evolution strategy, learning efficiency, organizational need, knowledge management, organisational aspects, trees (mathematics)",
• DOI = "doi:10.1109/ICHIT.2008.169",
• abstract = "Knowledge evolution is an important issue in knowledge management since enterprises face keen competition and need to keep the latest knowledge with time in an organization. In this paper, we proposed a GP-based knowledge-evolution framework to search for a good integrated classification tree with different evolving time points. The proposed approach can learn the evolving knowledge, integrating original and new knowledge, to deal properly with the organizational need for updating the latest knowledge as time goes on in a dynamic environment. In addition, we developed the initial population, consisting of four proportions, to accomplish suitable diversity and thus raise the search range as well as next learning efficiency in the evolutionary process.",
• notes = "Also known as \cite{4622798}",

}

Genetic Programming entries for Chan-Sheng Kuo Tzung-Pei Hong Samuel Chuen-Lung Chen

Citations