19. A computer implemented method in accordance with claim 2 wherein said method further comprises the steps of: a) Receiving said ill-defined problem domain of claim 18 , a set of SLT rules and higher order SLT rules derived from said ill-defined domain, wherein each said SLT rule has been made executable on a computer, and a set of problems, wherein said problem domain includes problems that cannot be solved by any one said higher or lower order SLT rule, b) Selecting a problem in said problem domain in step a), c) When said problem selected in step b) is solvable by one said SLT rule, providing tutoring on said problem in accordance with steps b) through l) in claim 2 , d) When said problem is solvable by exactly one of no said SLT rule and more than one said SLT rule, selecting one said higher order SLT rule in step a), wherein the range of said higher order SLT rule contains exactly one SLT rule that does solve said problem, and applying said higher order SLT rule to available SLT rules to generate a new SLT rule in said range, e) When said new SLT rule solves said problem, executing said new SLT rule on said problem.
19. A computer implemented method in accordance with claim 2 wherein said method further comprises the steps of: a) Receiving said ill-defined problem domain of claim 18 , a set of SLT rules and higher order SLT rules derived from said ill-defined domain, wherein each said SLT rule has been made executable on a computer, and a set of problems, wherein said problem domain includes problems that cannot be solved by any one said higher or lower order SLT rule, b) Selecting a problem in said problem domain in step a), c) When said problem selected in step b) is solvable by one said SLT rule, providing tutoring on said problem in accordance with steps b) through l) in claim 2 , d) When said problem is solvable by exactly one of no said SLT rule and more than one said SLT rule, selecting one said higher order SLT rule in step a), wherein the range of said higher order SLT rule contains exactly one SLT rule that does solve said problem, and applying said higher order SLT rule to available SLT rules to generate a new SLT rule in said range, e) When said new SLT rule solves said problem, executing said new SLT rule on said problem. 20. A computer implemented method in accordance with claim 19 wherein said higher order rules are domain specific instances of learning mechanisms commonly used in expert systems, wherein one commonly used learning mechanism is known as chaining, wherein outputs of successive rules serve as inputs for the next rule.