- author = "Robert Burbidge",
- title = "A Contribution to the Foundations of {AI}: Genetic Programming and Support Vector Machines",
- booktitle = "Workshop and Summer School on Evolutionary Computing Lecture Series by Pioneers",
- year = "2008",
- editor = "T. M. McGinnity",
- address = "University of Ulster",
- month = "18-20 " # aug,
- organisation = "School of Computing and Intelligent Systems, University of Ulster",
- keywords = "genetic algorithms, genetic programming, SVM",
-
URL = "
http://users.aber.ac.uk/rvb/wssec-rb-final.pdf",
- size = "4 pages",
- abstract = "The aim of genetic programming is to automatically find computer programs that solve problems; using an algorithm inspired by biological evolution. The aim of the support vector machine is to model empirical data; using an algorithm based on statistical optimality. Fundamentally, both these techniques, and all artificial intelligence disciplines, use search; with differing representations, search operators and objective functions. We formally compare these two techniques as a contribution toward the foundations of artificial intelligence, and less grandiosely, in order to encourage transfer of knowledge between the two disciplines.",
-
notes = "broken 2016
http://isel.infm.ulst.ac.uk/conference/wssec2008/
'The search space for GP is hard'. 'The search space for the SVM is easy'. 'inherent capacity control in GP' VC-dimension.",
