Efficient Genetic Programming for Finding Good Generalizing Boolean Functions

Created by W.Langdon from gp-bibliography.bib Revision:1.8154

@InProceedings{Droste:1997:eGPbf,

• author = "Stefan Droste",
• title = "Efficient Genetic Programming for Finding Good Generalizing {Boolean} Functions",
• booktitle = "Genetic Programming 1997: Proceedings of the Second Annual Conference",
• editor = "John R. Koza and Kalyanmoy Deb and Marco Dorigo and David B. Fogel and Max Garzon and Hitoshi Iba and Rick L. Riolo",
• year = "1997",
• month = "13-16 " # jul,
• keywords = "genetic algorithms, genetic programming",
• pages = "82--87",
• address = "Stanford University, CA, USA",
• publisher_address = "San Francisco, CA, USA",
• publisher = "Morgan Kaufmann",
• URL = "https://eldorado.uni-dortmund.de/dspace/bitstream/2003/5323/1/gp97.pdf",
• URL = "http://citeseer.ist.psu.edu/326196.html",
• size = "pages",
• abstract = "This paper shows how genetic programming (GP) can help in finding generalizing Boolean functions when only a small part of the function values are given. The selection pressure favours functions having as few subfunctions as possible while only using essential variables, so the resulting functions should have good generalization properties. For efficiency no S-expressions are used for representation, but a special case of directed acyclic graphs known as ordered binary decision diagrams (OBDDs), making it possible to learn the 20-multiplexer.",
• notes = "GP-97",

}

Genetic Programming entries for Stefan Droste

Citations