17. The method of claim 11 wherein said step of generating a matrix of learning coefficients comprises the steps of: (a) randomly selecting one of said training examples: (b) testing, for each resultant variable which is provided a value in said training example, matrix values in a temporary matrix of learning coefficients associated with said resultant variable to determine whether the matrix values combine with the variable values of the example to determine the proper response for the resultant variable as provided by the training example; (c) replacing the matrix values associated with a resultant variable in said matrix of learning coefficients with the matrix values for said resultant variable from said temporary matrix of learning coefficients when said temporary matrix values have determined the correct response for a greater number of training examples than had been determined by the original matrix of learning coefficients; (d) modifying the matrix values associated with a resultant variable in the temporary matrix of learning coefficients when said matrix values determine an incorrect response for the training example; and (e) repeating steps a-d at least a predetermined number of times.
19. The method of claim 17 wherein said learning method further comprises counting the number of consecutive times the temporary matrix values associated with each resultant variable arise at the correct response for the resultant variable as provided by an example.