Solving Symbolic Regression Problems using Incremental Evaluation in Genetic Programming

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

@InProceedings{Hoang:2006:CEC,

• author = "Tuan-Hao Hoang and Daryl Essam and R. I. (Bob) McKay and Xuan Hoai Nguyen",
• title = "Solving Symbolic Regression Problems using Incremental Evaluation in Genetic Programming",
• booktitle = "Proceedings of the 2006 IEEE Congress on Evolutionary Computation",
• year = "2006",
• pages = "7487--7494",
• address = "Vancouver",
• month = "16-21 " # jul,
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming, TAG, SYM_GP, building block, polynomial symbolic regression, Fourier series",
• ISBN = "0-7803-9487-9",
• URL = "http://seal.tst.adfa.edu.au/~z3106820/publications/cec2006.devtag.pdf",
• DOI = "doi:10.1109/CEC.2006.1688570",
• size = "8 pages",
• abstract = "we show some experimental results using Incremental Evaluation with Tree Adjoining Grammar Guided Genetic Programming (DEVTAG) on two symbolic regression problems, a benchmark polynomial fitting problem in genetic programming, and a Fourier series problem (saw-tooth problem). In our pilot study, we compare results with standard Genetic Programming (GP) and the original Tree Adjoining Grammar Guided Genetic Programming (TAG3P). Our results on the two problems are good, outperforming both standard GP and the original TAG3P.",
• notes = "WCCI 2006 - A joint meeting of the IEEE, the EPS, and the IEE.",

}

Genetic Programming entries for Tuan-Hao Hoang Daryl Essam R I (Bob) McKay Nguyen Xuan Hoai

Citations