Expert Systems VI

Advantages and disadvantages

Advantages:

§  Provides consistent answers for repetitive decisions, processes and tasks

§  Holds and maintains significant levels of information

§  Encourages organizations to clarify the logic of their decision-making

§  Always asks a question, that a human might forget to ask

§  Can work continuously (no human needs)

§  Can be used by the user more frequently

§  A multi-user expert system can serve more users at a time

 Disadvantages:

§  Lacks common sense needed in some decision making

§  Cannot respond creatively like a human expert would in unusual circumstances

§  Domain experts not always able to explain their logic and reasoning

§  Errors may occur in the knowledge base, and lead to wrong decisions

§  Cannot adapt to changing environments, unless knowledge base is changed

 

Types of problems solved by expert systems

Expert systems are most valuable to organizations that have a high-level of know-how experience and expertise that cannot be easily transferred to other members. They are designed to carry the intelligence and information found in the intellect of experts and provide this knowledge to other members of the organization for problem-solving purposes.

Typically, the problems to be solved are of the sort that would normally be tackled by a medical or other professional. Real experts in the problem domain (which will typically be very narrow, for instance "diagnosing skin conditions in human teenagers") are asked to provide "rules of thumb" on how they evaluate the problems, either explicitly with the aid of experienced systems developers, or sometimes implicitly, by getting such experts to evaluate test cases and using computer programs to examine the test data and (in a strictly limited manner) derive rules from that. Generally, expert systems are used for problems for which there is no single "correct" solution which can be encoded in a conventional algorithm — one would not write an expert system to find shortest paths through graphs, or sort data, as there are simply easier ways to do these tasks.

Simple systems use simple true/false logic to evaluate data. More sophisticated systems are capable of performing at least some evaluation, taking into account real-world uncertainties, using such methods as fuzzy logic. Such sophistication is difficult to develop and still highly imperfect.

 

Expert Systems Shells or Inference Engine

A shell is a complete development environment for building and maintaining knowledge-based applications. It provides a step-by-step methodology, and ideally a user-friendly interface such as a graphical interface, for a knowledge engineer that allows the domain experts themselves to be directly involved in structuring and encoding the knowledge. Many commercial shells are available, one example beingeGanges which aims to remove the need for a knowledge engineer.