Mathematics By Objective  (MBO)

Utilizing Conman's Laws of Browness, a new application was proposed by Advocate (1971).  Advocate reasoned that by assuming a result one could derive coefficients or data sets within the Brown Space  (also referred to as the Brown Domain)  that would satisfy the Laws of Browness.  Such a procedure would provide optimum Browness as well as the desired result.  Advocate (1975) further proposed that the sophistication of the analysis technique was significant to the application of her procedure.  Advocate created a new measure of a Brown number that was directly proportional to the number of calculations performed on the data set.  Advocate used the term "oder" which was ranked from None (Oder = 100 or more)  to Strong (Oder = 0).  Although still in use today, the term "oder" is probably a typographic error misspelling of "order". Advocate established that the basis for distinguishing oder values on the order of magnitude of the number of calculations performed.  This new measure has lead to a more detailed description of a Brown Number.

Consider assuming a single number at random.  Such a number would be Very Brown (Br = 1.0, or saturated Browness, Bs).  Since no calculations were involved, Oder = 0 and the number could be more correctly described as "Strongly Brown".  Consider assuming 500 numbers at random.  Using a computer, manipulate the numbers 100 times.  The result would still be Brown (Br = 1.0) but the Oder =100 and the number is correctly termed a Oderless Brown Number (OBN).

Advocate further postulated that oder should be minimized to "maximize gains from low reliability data sets".  The innovative application of the Second Law allowed the creation of a new type of Brown Number:  One that the producer knew was Brown but no one else could determine without enormous effort.  Borrowing from computer sciences, Advocate termed this effect "Browness Hiding".

Adman's  (1976) built on Advocate's work and further developed computer applications of Brown Numbers.  His applications were specifically designed to "hide" Brown Numbers by attempting to reduce Oder by using interesting neural network algorithms.  Because of the variations in the decision techniques, the work is closely related to “Fuzzy Mathematics.” Adman coined this approach as “Fuzzy Thinking”.

(c) 1982, 2009 Jorge Branche, Jr.