Abstract:
Researchers have developed artificially intelligent (AI) and expert systems (ES) to assist in the formulation, solution and interpretation of generic mathematical programs (MP). In addition, researchers also have built domain-specific systems either modeled around a mathematical program or which include a mathematical program module. In these systems, the specificity of the domain allows researchers to extend the interpretation or formulation beyond that available from the generic set of assumptions about mathematical programming. Further, researchers have begun to investigate the use of mathematical program formulations of expert systems. The purpose of their research has been to, e.g., understand the complexity of the expert systems and also to examine the feasibility of mathematical programming as an alternative solution methodology for those expert systems. This paper surveys and extends some of that literature that integrates AIlES and MP, and elicits some of the current research issues of concern.
Interesting to see so many ideas we take for granted in AI being developed in infancy here.
For example, CBR seems to be describing a simplified version of what we would call Machine Learning today:
Case-based reasoning (CBR) involves the process of making decisions based on specific examples of what has occurred in the past, rather than a set of rules. Previous cases or plans are stored for use in solving future problems. In addition, means of adapting previous decision making· problems are saved. By making previous solutions available to decision makers, the decision maker can anticipate variables of concern and alternative solutions. In addition, past mistakes can be avoided, while short-cuts can be made available. As noted by Hammond [1988, p.17], the ideas behind case-based planning rise out of the simple principle:
If it worked, use it again, and a corollary; if it works, don’t worry about it.
The refinements of the basic idea come out of a second, equally simple principle:
If it didn’t work, remember not to do it again, to which is added: If it doesn’t work, fix it.
Here again, we would take this totally for granted:
There are at least two implications of coupling a mathematical program in an Al/ES system. First, coupling MP and AI/ES indicates that the expertise of the operation research analyst can be captured in a computer program. This suggests that the design, formulation, interpretation and management of those MP can be formulated as a program. Initially, it was unclear as to the ability of developers to accomplish that task. As seen in Sections 3 and 4, there should be no question regarding that task. This also indicates that there probably is no more need to develop prototypes simply to test the ability to develop programs of this sort.