A case study where biology inspired a solution to a computer science problem

Created by W.Langdon from gp-bibliography.bib Revision:1.8187

@InProceedings{koza:1996:biscsp,

• author = "John R. Koza and David Andre",
• title = "A case study where biology inspired a solution to a computer science problem",
• booktitle = "Pacific Symposium on Biocomputing '96",
• year = "1996",
• editor = "Lawrence Hunter and Teri E. Klein",
• pages = "500--511",
• publisher_address = "Singapore",
• publisher = "World Scientific",
• keywords = "genetic algorithms, genetic programming",
• URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.368.6585",
• URL = "http://www.genetic-programming.com/jkpdf/psb1996.pdf",
• abstract = "This paper describes how the biological theory of gene duplication described in Susumu Ohno's provocative book, Evolution by Means of Gene Duplication, was brought to bear on a vexatious problem from the domain of automated machine learning, namely the problem of architecture discovery. An automatic programming system should require that the user make as few problem-specific decisions as possible concerning the size, shape, and character of the ultimate solution to the problem. Six new architecture-altering operations enable genetic programming to automatically discover an appropriate architecture for solving the problem concurrently with its efforts to solve the problem. These architecture-altering operations were motivated by the way that new biological structures, functions, and behaviors arise in nature using gene duplication. Genetic programming with the new architecture-altering operations was then applied to the transmembrane protein segment identification problem. The out-of-sample error rate for the best genetically-evolved program achieved was slightly better than that of previously-reported human-written algorithms for this problem.",
• notes = "PSB 96",

}

Genetic Programming entries for John Koza David Andre

Citations