>The prime example of this is the evolutionary process. Information
>transmitted from generation to generation in the form of DNA is changed
>randomly ("noise") as a result of mutation. This "noise" is what drives
>continual adaptation to a changing environment.
>
>Genetic algorithms have show that there is an optimum rate for mutation.
>Too little or too much reduces the "learning" that the system does.
Do you suppose it is the "noise" that generates the "choice" array for the
selection edge preceding the newly-established order?
--- Jim Campbell e-mail: CAMPBELL@upanet.uleth.ca Public Access Internet - via the University of Lethbridge 190 Oxford Rd. West Phone & Fax: (403) 381 3774 Lethbridge, Alberta Myers-Briggs Type: ENTP Canada T1K 4V4"Life-learning: creating new forms, not diminishing the possibilities"