Routine high-return human-competitive machine learning

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@InProceedings{Koza:2003:ICMLA,

• author = "John R. Koza",
• title = "Routine high-return human-competitive machine learning",
• booktitle = "Proceedings of the International Conference on Machine Learning and Applications",
• year = "2003",
• editor = "M. Arif Wani and K. Cois and K. Hafeez",
• pages = "6--12",
• address = "Los Angeles",
• keywords = "genetic algorithms, genetic programming, machine learning, automated invention, parameterized topology, human-competitive",
• URL = "http://www.genetic-programming.com/jkpdf/icmla2003.pdf",
• size = "7 pages",
• abstract = "Genetic programming is a systematic method for getting computers to automatically solve a problem. Genetic programming starts from a high-level statement of what needs to be done and automatically creates a computer program to solve the problem. The paper makes the points that (1) genetic programming now routinely delivers high-return human-competitive machine intelligence; (2) it is an automated invention machine; (3) it can automatically create a general solution to a problem in the form of a parameterised topology; and (4) it has delivered a progression of qualitatively more substantial results in synchrony with five approximately order-of-magnitude increases in the expenditure of computer time.",

}

Genetic Programming entries for John Koza

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