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Expert Systems. User interface. Reasoning. Control. Inference engine. user. Knowledge base. 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
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User interface Reasoning Control Inference engine user Knowledge base 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
Artificial Intelligence • 'Artificial intelligence is the science of making machines do things that would require intelligence if done by humans’ Watch a video
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
Yes Yes Smell fuel? No No Yes No Engine flooded: try starting car in 10 mins Does starter work? Does battery work? Is fuel tank empty? Get car to garage Recharge battery Yes No Fill tank with fuel Blockage: get car to garage
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