- author = "Frederic Gruau",
- title = "Genetic Synthesis of Modular Neural Networks",
- year = "1993",
- booktitle = "Proceedings of the 5th International Conference on Genetic Algorithms, ICGA-93",
- editor = "Stephanie Forrest",
- publisher = "Morgan Kaufmann",
- pages = "318--325",
- month = "17-21 " # jul,
- address = "University of Illinois at Urbana-Champaign",
- keywords = "genetic algorithms, genetic programming, ANN, Mux, parity distributed population",
- ISBN = "1-55860-299-2",
- acmid = "657409",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/icga93_gruau.pdf",
-
URL = "
http://dl.acm.org/citation.cfm?id=645513.657409",
- size = "8 pages",
- abstract = "Cellular encoding is a method for encoding families of Boolean neural networks having the same same structure, that can compute scalable Boolean functions. The current study describes how to incorporate modularity into Cellular Encoding. A Genetic Algorithm is used to find part of a modular code that yields both architecture and plus-minus 1 weights specifying the decoder Boolean function of 10 inputs and 1024 outputs. This results suggests that the GA can exploit modularity in order to find architectures within a more complex range",
-
notes = "'solves the decoder of L inputs for arbitary large
L'
",
