GP with Ranging-Binding Technique for Symbolic Regression

Created by W.Langdon from gp-bibliography.bib Revision:1.7686

@InProceedings{fang:2023:GECCOcomp,

• author = "Wen-Zhong Fang and Chi-Hsien Chang and Jung-Chun Liu and Tian-Li Yu",
• title = "{GP} with {Ranging-Binding} Technique for Symbolic Regression",
• booktitle = "Proceedings of the 2023 Genetic and Evolutionary Computation Conference",
• year = "2023",
• editor = "Sara Silva and Luis Paquete and Leonardo Vanneschi and Nuno Lourenco and Ales Zamuda and Ahmed Kheiri and Arnaud Liefooghe and Bing Xue and Ying Bi and Nelishia Pillay and Irene Moser and Arthur Guijt and Jessica Catarino and Pablo Garcia-Sanchez and Leonardo Trujillo and Carla Silva and Nadarajen Veerapen",
• pages = "563--566",
• address = "Lisbon, Portugal",
• series = "GECCO '23",
• month = "15-19 " # jul,
• organisation = "SIGEVO",
• publisher = "Association for Computing Machinery",
• publisher_address = "New York, NY, USA",
• keywords = "genetic algorithms, genetic programming, evolutionary computation: Poster",
• isbn13 = "9798400701191",
• DOI = "doi:10.1145/3583133.3590605",
• size = "4 pages",
• abstract = "This paper proposes a model-based genetic programming algorithm for symbolic regression, called the ranging-binding genetic programming algorithm (RBGP). The goal is to allow offspring to retain the superiority of their promising parents during evolution. Inspired by the concept of model building, RBGP makes use of syntactic information and semantics information in a program to capture the hidden patterns. When compared with GP-GOMEA, ellynGP, and gplearn, RBGP outperformed the others on average in the Penn machine learning benchmarks, RBGP achieving statistically significant improvements over all other methods on 44 percent of the problems.",
• notes = "GECCO-2023 A Recombination of the 32nd International Conference on Genetic Algorithms (ICGA) and the 28th Annual Genetic Programming Conference (GP)",

}

Genetic Programming entries for Wen-Zhong Fang Chi-Hsien Chang Jung-Chun Liu Tian-Li Yu

Citations