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ICT IGCSE.  Understand the use of expert systems in  Mineral prospecting  Car engine fault diagnosis  Medical diagnosis  Oil/mineral prospecting.

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Presentation on theme: "ICT IGCSE.  Understand the use of expert systems in  Mineral prospecting  Car engine fault diagnosis  Medical diagnosis  Oil/mineral prospecting."— Presentation transcript:

1 ICT IGCSE

2  Understand the use of expert systems in  Mineral prospecting  Car engine fault diagnosis  Medical diagnosis  Oil/mineral prospecting  Plant/animal identification  Strategy games eg Chess

3  An expert system is computer software that attempts to act like a human expert on a particular subject area.  Expert systems are often used to advise non- experts in situations where a human expert is unavailable (for example it may be too expensive to employ a human expert, or it might be a difficult to reach the location).

4  Diagnosing a person’s illness  Diagnostics (car engine faults, circuit board faults etc)  Prospecting for oil and minerals  Tax and financial calculations  Chess games  Identification of plants, animals, chemical compounds  Road scheduling for delivery vehicles

5  An expert system is a knowledge-based system which attempts to replace a human 'expert' in a particular field. The system will consist of  a large database of knowledge  facilities for searching the knowledge database  a set of rules for making deductions from the data  An engine to apply those rules (inference engine)

6 An expert system is made up of four parts:  A user interface  A knowledge base  A rules base  An inference engine

7  This is the system that allows a non-expert user to query (question) the expert system, and to receive advice. The user- interface is designed to be a simple to use as possible.

8  This is a collection of facts. The knowledge base is created from information provided by human experts.  It is a database designed to allow the complex storage and retrieval requirements of the expert systems

9  This is made up of a series of ‘inference rules’  IF the country is in South America  AND the language is Portuguese,  THEN the country must be Brazil  These inference rules are used by the inference engine to draw conclusions.  The inference rules closely follow human reasoning.

10  This acts rather like a search engine, examining the knowledge base for information that matches the user's query.  It is software that attempts to derive answers from the knowledge base using a form of reasoning.

11

12  The non-expert user queries the expert system. This is done by asking a question, or by answering questions asked by the expert system.  The inference engine uses the query to search the knowledge base and then provides an answer or some advice to the user.

13  Medical diagnosis (the knowledge base would contain medical information, the symptoms of the patient would be used as the query, and the advice would be a diagnose of the patient’s illness)

14  Playing strategy games like chess against a computer (the knowledge base would contain strategies and moves, the player's moves would be used as the query, and the output would be the computer's 'expert' moves)

15  Providing financial advice - whether to invest in a business, etc. (the knowledge base would contain data about the performance of financial markets and businesses in the past)

16  Helping to identify items such as plants / animals / rocks / etc. (the knowledge base would contain characteristics of every item, the details of an unknown item would be used as the query, and the advice would be a likely identification)

17  Helping to discover locations to drill for water / oil (the knowledge base would contain characteristics of likely rock formations where oil / water could be found, the details of a particular location would be used as the query, and the advice would be the likelihood of finding oil / water there)

18  Helping to diagnose car engine problems (like medical diagnosis, but for cars!)  Two types:  Onboard  In workshops

19  Human experts make mistakes all the time (people forget things, etc.) so you might imagine that a computer-based expert system would be much better to have around.

20  An ES can store far more information than a human.  Expert systems provide consistent answers.  ES does not 'forget’ to ask important questions, or make mistakes.  Reduces the time taken to solve a problem  Data can be kept up-to-date.

21  Data can be collected from many experts  The expert system is always available 24 hours a day and will never 'retire'.  The system can be used at a distance over a network.  A less skilled workforce is needed  Opportunity to save money  People/areas can access expertise they couldn’t otherwise afford

22  Very expensive to set up in the first place  The computer’s reasoning is only as good as the rules it has been given  They have no 'common sense' (a human user tends to notice obvious errors, whereas a computer wouldn't)

23  Errors in the knowledge base can lead to incorrect decisions being made  Mistakes made when entering facts/answers to questions can lead to incorrect decisions  Not possible to break ALL expert knowledge into facts, rules & probabilities  No human interaction/human touch  Considerable training is required to ensure the system is used correctly by the operators


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