- author = "Jan Jannink",
- title = "Cracking and Co-Evolving Randomizers",
- booktitle = "Advances in Genetic Programming",
- publisher = "MIT Press",
- editor = "Kenneth E. {Kinnear, Jr.}",
- year = "1994",
- chapter = "20",
- pages = "425--443",
- keywords = "genetic algorithms, genetic programming, memory",
-
URL = "
http://infolab.stanford.edu/pub/jannink/gp.ps",
-
URL = "
http://www.amazon.co.uk/Advances-Genetic-Programming-Complex-Adaptive/dp/0262111888",
-
URL = "
http://cognet.mit.edu/sites/default/files/books/9780262277181/pdfs/9780262277181_chap20.pdf",
-
DOI = "
doi:10.7551/mitpress/1108.003.0026",
- size = "19 pages",
- abstract = "Although pseudo-random number generator or randomizers are of great importance in the domain of simulating real world phenomena, it is difficult to construct functions which satisfy the many criteria, such as uniform distribution, which good randomizers possess. It is computationally expensive perform the statistical analysis required to establish their quality. Moreover, no current method of analysis can guarantee quality, since even the question of what constitutes the set of criteria defining randomness remains open. ...",
-
notes = "Uses protect mod. But doesnt give details.Uses
Teller's READ and WRITE Uses IFGEN macro to evolve two
separate functions in same tree Ref Kolmogorov (1965) =
on density of information packing Ref James (1990) = on
very long (10**170) sequence random numbers Initilises
so store[x]=x+1 rather than zero.
Part of \cite{kinnear:book}",
