28. A learning process for operating a general purpose computer having a knowledge base including a matrix of learning coefficients, which includes a matrix value for each combination of one of a set of resultant variables and one of a set of primary variables, to enhance said matrix, comprising the steps of: (a) inputting a set of examples, each example including values for at least one primary variable and values for at least one resultant variable; (b) randomly selecting one of said examples; (c) testing, for each resultant variable which is provided a value in said example, matrix values in a temporary matrix of learning coefficients associated with said resultant variable to determine whether the matrix values combine with the primary variable values of the example to determine the proper value of said resultant variable as provided by the example; (d) 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 value for said resultant variable for a greater number of examples than had been correctly determined by the present matrix of learning coefficients; (e) modifying the temporary matrix values associated with a resultant variable in the temporary matrix of learning coefficients when said temporary matrix values determine an incorrect response for the examples; and (f) repeating steps b-e at least a predetermined number of times.
28. A learning process for operating a general purpose computer having a knowledge base including a matrix of learning coefficients, which includes a matrix value for each combination of one of a set of resultant variables and one of a set of primary variables, to enhance said matrix, comprising the steps of: (a) inputting a set of examples, each example including values for at least one primary variable and values for at least one resultant variable; (b) randomly selecting one of said examples; (c) testing, for each resultant variable which is provided a value in said example, matrix values in a temporary matrix of learning coefficients associated with said resultant variable to determine whether the matrix values combine with the primary variable values of the example to determine the proper value of said resultant variable as provided by the example; (d) 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 value for said resultant variable for a greater number of examples than had been correctly determined by the present matrix of learning coefficients; (e) modifying the temporary matrix values associated with a resultant variable in the temporary matrix of learning coefficients when said temporary matrix values determine an incorrect response for the examples; and (f) repeating steps b-e at least a predetermined number of times. 30. The learning process of claim 28 further comprising the step of counting the number of consecutive times the temporary matrix values associated with each resultant variable determine the correct response for the resultant variable as provided by an example.