Guidelines for defining benchmark problems in Genetic Programming

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

@InProceedings{nicolau:cec2015,

• author = "Miguel Nicolau and Alexandros Agapitos and Michael O'Neill and Anthony Brabazon",
• title = "Guidelines for defining benchmark problems in Genetic Programming",
• booktitle = "Proceedings of 2015 IEEE Congress on Evolutionary Computation (CEC 2015)",
• editor = "Yadahiko Murata",
• pages = "1152--1159",
• year = "2015",
• address = "Sendai, Japan",
• month = "25-28 " # may,
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/CEC.2015.7257019",
• abstract = "The field of Genetic Programming has recently seen a surge of attention to the fact that benchmarking and comparison of approaches is often done in non-standard ways, using poorly designed comparison problems. We raise some issues concerning the design of benchmarks, within the domain of symbolic regression, through experimental evidence. A set of guidelines is provided, aiming towards careful definition and use of artificial functions as symbolic regression benchmarks.",
• notes = "1145 hrs 15594 CEC2015",

}

Genetic Programming entries for Miguel Nicolau Alexandros Agapitos Michael O'Neill Anthony Brabazon

Citations