FREE online courses on Expert Systems - Expert Systems

 

Expert systems are computer applications, which embody some non-algorithmic expertise for solving certain types of problems. For example, expert systems are used in diagnostic applications servicing both people and machinery. They also play chess, make financial planning decisions, configure computers, monitor real time systems, underwrite insurance policies, and perform many other services, which previously required human expertise.

Figure 1.1:  Expert system components and human interfaces

Expert systems have a number of major system components and interface with individuals in various roles. These are illustrated in figure 1.1. The major components are:

 

Knowledge base - a declarative representation of the expertise, often in IF THEN rules;

Working storage - the data which is specific to a problem being solved;

Inference engine - the code at the core of the system which derives recommendations from the knowledge base and problem-specific data in working storage;

User interface - the code that controls the dialog between the user and the system.

 

To understand expert system design, it is also necessary to understand the major roles of individuals who interact with the system. These are:

 

Domain expert - the individual or individuals who currently are experts solving the problems the system is intended to solve;

Knowledge engineer - the individual who encodes the expert's knowledge in a declarative form that can be used by the expert system;

User - the individual who will be consulting with the system to get advice which would have been provided by the expert.

 

Many expert systems are built with products called expert system shells. The shell is a piece of software which contains the user interface, a format for declarative knowledge in the knowledge base, and an inference engine. The knowledge engineer uses the shell to build a system for a particular problem domain.

Expert systems are also built with shells that are custom developed for particular applications. In this case there is another key individual:

 

System engineer - the individual who builds the user interface, designs the declarative format of the knowledge base, and implements the inference engine.

 

Depending on the size of the project, the knowledge engineer and the system engineer might be the same person. For a custom built system, the design of the format of the knowledge base, and the coding of the domain knowledge are closely related. The format has a significant effect on the coding of the knowledge.

 

One of the major bottlenecks in building expert systems is the knowledge engineering process. The coding of the expertise into the declarative rule format can be a difficult and tedious task. One major advantage of a customized shell is that the format of the knowledge base can be designed to facilitate the knowledge engineering process.

 

The objective of this design process is to reduce the semantic gap. Semantic gap refers to the difference between the natural representation of some knowledge and the programmatic representation of that knowledge. For example, compare the semantic gap between a mathematical formula and its representation in both assembler and FORTRAN. FORTRAN code (for formulas) has a smaller semantic gap and is therefore easier to work with.

 

Since the major bottleneck in expert system development is the building of the knowledge base, it stands to reason that the semantic gap between the expert's representation of the knowledge and the representation in the knowledge base should be minimized. With a customized system, the system engineer can implement a knowledge base whose structures are as close as possible to those used by the domain expert.

 

This course concentrates primarily on the techniques used by the system engineer and knowledge engineer to design customized systems. It explains the various types of inference engines and knowledge bases that can be designed, and how to build and use them. It tells how they can be mixed together for some problems, and customized to meet the needs of a given application.