10/20/08 class notes

Notes on Expert Systems
http://en.wikipedia.org/wiki/Expert_systems

Expert Systems
- a system that performs on a knowledge base
- contains the specific knowledge that is contributed by someone who has many years experience in that domain
- sub-field of artificial intelligence
- simultaneous processing
- knowledge representation
-- cognitive science
- forward chaining
-- starts with the data available and uses the inference rules to conclude more data until a desired goal is reached
- backwards chaining
-- starts with a list of goals and works backwards to see if there is data which will allow it to conclude any of these goals
- Certainty Factors
-- One advantage of expert systems over traditional methods of programming is that they allow the use of "confidences" (or "certainty factors"). When a human reasons he does not always conclude things with 100% confidence. He might say, "If Fritz is green, then he is probably a frog" (after all, he might be a chameleon). This type of reasoning can be imitated by using numeric values called confidences. For example, if it is known that Fritz is green, it might be concluded with 0.85 confidence that he is a frog; or, if it is known that he is a frog, it might be concluded with 0.95 confidence that he hops. These numbers are similar in nature to probabilities, but they are not the same. They are meant to imitate the confidences humans use in reasoning rather than to follow the mathematical definitions used in calculating probabilities.
-Application of Expert systems
--Expert systems are designed and created to facilitate tasks in the fields of accounting, medicine, process control, financial service, production, human resources etc. Indeed, the foundation of a successful expert system depends on a series of technical procedures and development that may be designed by certain technicians and related experts.
-does not process invoices
-does not process incoming messages
-not a technology that replaces all other technology
-does what other technology doesn't do
-applies human intelligence, experience, and skills that requires high knowledge to solve
-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
---Never "forgets" to ask a question, as a human might
--Disadvantages
---Lacks common sense needed in some decision making
---Cannot make creative responses as 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.


Dr. Jih's comments
-converting tacit -> explicit knowledge is always difficult
-time consuming process
-very important task
-expert can only be present at one time in only one location, once the expert knowledge gets transferred into expert systems its available in multiple locations and multiple times, that is the greatest benefit
-high power problem solving capability
-never forgets to ask a question
-no difference between Monday and Friday
-expert system doesn't get sick or go on strike
-needs to be updated
-keeps on provided high level value information every time you use it
-does not know anything outside of the knowledge base
-knowledge base must be maintained