Expert Systems

Knowledge base Inference engine ReasoningControl User interface user Components of an rule based Expert System

Learning Objectives What you need to know about expert systems What expert systems are The purpose of expert systems The components of expert systems The applications of expert systems The advantages and disadvantages of expert systems The social, legal and ethical issues of using expert systems

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An Expert System An expert system is a computer program that has access to a large database of knowledge about one particular subject

The purpose of an expert system To contain the knowledge of a human expert To be able to present the knowledge in a useful way To be able to describe how it came to it’s conclusions In other words to mimic a human expert

Components of an expert system The knowledge base The inference engine The interface

The knowledge base A large database Contains facts Contains rules on how facts should be used in any given situation

The inference engine The expert system program Uses the facts Applies the rules Comes to conclusions

No Does starter work? No Get car to garage Does battery work? Yes No Recharge battery Smell fuel? Yes No Is fuel tank empty? Fill tank with fuel Blockage: get car to garage Yes Engine flooded: try starting car in 10 mins

The explanatory interface Allows communication between the inference engine and the user Asks question of the user Allows the user to ask questions Explains why it has reached a conclusion or decision

Applications of expert systems Medical –MYCIN blood diseases –PUFF lung disease –BTDS brain tumours –5GL diagnosis

Applications of expert systems Geological Archaeological Car Mechanics Chemical analysis

Advantages of an expert system Save money Save time Accessible Accumulated knowledge of many experts Consistent Does not forget things Not subjective (not biased)

Disadvantages of an expert system Expensive to produce Time consuming Lacks depth Inflexible No common sense Programs have errors

Disadvantages of an expert system Expensive to produce –It costs a lot to employ experts to part with their knowledge you have to pay for their time –Costs a lot to employ programmers to write the program and designers to develop the interface Time consuming –It takes a lot of time to extract the information –To set up the database –To create the inference engine

Disadvantages of an expert system Lacks depth –The total knowledge of an expert cannot be completely replicated, people remember things in different ways. The ES cannot make connections which help it to remember. Inflexible –ES can only act within the rules –they have fixed response

Disadvantages of an expert system No common sense –Cannot think for themselves, everything must be programmed. ES cannot use the facts and rules to come to conclusions based on their own experience as they have no capacity to add in to their knowledge base Programs have errors which will only be known about when something goes wrong –With an ES the “wrong” could be disastrous e.g. in a medical situation