Expert Systems

1. Expert Systems 3.3.4

2. The aim of this presentation • You will be able to: • Explain what is meant by an expert system and describe its components and applications.

3. Introduction • Society is becoming more complex. • More and more information is becoming available. • Systems need to be designed to deal with information so that it can be found more easily by humans.

4. What is an expert system? • Alternative name is knowledge-based system. • Consider: • The problem of diagnosing a patient’s illness. • Doctors can break down the symptoms and use their knowledge and possibly tests on the patient to try and figure out what the probably illness is. • Sometimes it takes a team of doctors to work out what the problem is.

5. What is an expert system? • Now consider: • A computer that has all the information stored about every illness known to man. • It stores information such as symptoms and treatments. • As a patient describes their symptoms the doctor can input these into the system and the computer displays all the illnesses that match up with the symptoms. • Using the new facts the doctor can eliminate tests that do not need to be carried out and it lowers the risk of mis-diagnosing patients.

6. Advantages • Expert systems usually contain the knowledge of a large number of specialists. • They can search through information very quickly  much faster than a human. • Less likely to forget details about rare diseases, unlike a human. • Could be used by people to decide if they need to go to the doctors or not. • A bit like the family doctor books!

7. Disadvantages • Can sometimes be expensive to be set up. • They still rely on accurate information being put into the system. One mistake could be costly! • Useless if asked questions outside their knowledge bank. • Can people really trust a machine??

8. Next Generation • Will compose of a natural language interface. • The ultimate aim is to be able to hold a conversation with a computer. • The Turning Test • Alan Turning developed a simple test to see if a computer possessed intelligence. • People had to work out if they were talking to another person or a computer. • Most people realised that it was a computer.

9. The medical problem revisited • Symptoms tend to exist for many types of illnesses. • It is unlikely that the expert system will find one illness that meets all the criteria. • Multiple responses may be given for a headache, high temperature and cough for example: • Common Cold = 61.78% chance • Influenza = 38.21% chance • Bubonic plague = 0.01% chance

10. What makes up an expert system? • There are four parts to an expert system: • The knowledge base • The rule base • The inference engine • The user interface

11. The system  The knowledge base The inference engine The user interface The rule base user

12. The knowledge base • This sections holds the facts. • It will hold information related to the topic that the expert system is intended for.

13. The rule base • This section holds rules that need to be applied to the knowledge base. • For example: • IF a toe nail is swollen • AND the nail is black OR there is puss • THEN it could be an in-growing toenail.

14. The inference engine • This is the brains of the system. • It is where all the clever bits happen. • It separates the user interface from the clever bit of the system. • It allows different user interfaces to be created to suit different needs…the knowledge base remains the same…its only the interface that changes.

15. The user interface • The user will need an interface through which they can interact with the system. • The interface may display closed questions which will result in different responses being displayed. • One day open ended questions might be accepted.

16. Types of knowledge-based system • For each type you will need to be able to describe an example. • Diagnostic systems • Advice-giving systems • Decision making systems

17. Diagnostic systems • Asks a question to narrow down the number of results from the knowledge bank. • Classic example is the medical system we have already covered. • Consider the following diagram and note how the knowledge bank gets smaller. Question 1 Question 2 Question 3 Yes Yes Knowledge bank Yes No No Yes No No Yes Yes No No Yes No

18. Advice-giving systems • A stock monitoring system is a good example of this. • It monitors the level of stock and then when levels drop too low it will advise that stock may need to be reordered. • This would then be done manually if they want to continue stocking that particular product.

19. Decision-making systems • A more advanced system compared to advice-giving systems. • Taking the stock example again: • Stock can be reordered automatically when conditions meet specified requirements such as: • Stock level falls below a set level • Time of year and market trends • Number of sales in recent days, weeks, months etc • Etc…

20. Questions • Define a ‘knowledge-based system’ • Describe the parts that make up a knowledge-based system, using examples where you can. • What are the characteristics of an expert system? • State three types of knowledge-based system and give examples of each. • What is the essential difference between an advice-giving system and a decision-making system? • Describe the pros and cons of introducing a medical expert system into a third world country in place of a doctor.