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Artificial Intelligence & Expert Systems

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Presentation on theme: "Artificial Intelligence & Expert Systems"— Presentation transcript:

1 Artificial Intelligence & Expert Systems

2 Definition of artificial Intelligence
Conventional data processing is concerned with inputting and processing data in the form of fact and figures in order to produce operational or management information. Artificial intelligence, on the other hand, is based on knowledge. A widely accepted definition of artificial intelligence is based on a test devised by Alan Turing in 1950: Suppose there are two identical terminals in a room, one connected to a computer, and the other operated remotely by a person. If someone using the two terminals is unable to tell which is connected to the computer and which is operated by thee person, the computer can be credited with intelligence. Competitions are regularly held in which judges “talk” via terminals to a mixture of computer systems and people and try to guess which is which. In one such contest held in Boston in August 1991, where questions were limited to a small range of specific topics, two People and six programs were tested against six judges. Four programs convinced at least one judge that they were people. Two judges mistook one of the people, Cynthia Clay, for a program. They didn’t believe anyone would know that much about Shakespeare. Q1: Write down three questions you could pose in order to distinguish between the computer and the human.

3 Neural Computing The technology that makes this possible is neural computing, the revolutionary process that mimics the way the human brain works. By imitating the way that thought processes pass through the neurons and synapses of the brain, reinforcing some signals and dissipating others, neural computing enable machines to retain the most important information and discard the rest. This self-teaching ability sets them apart from traditional computers which cannot reprogram themselves. Neural computing is being used in a wide variety of applications. Bass the brewers for example, has built (with the aid of scientists at Warwick University) a machine that can sniff the beer and decide if it is up to scratch. Its artificial nose makes a complex series of judgements based on electro-chemical stimuli received by its gas sensors. By detecting an over-active yeast or a weak crop of hops at an early stage in the fermentation process, the “nose” could save the brewers from having to throw away a whole batch of 345,600 pints of beer. Bankers, stockbrokers and insurance agents are all experimenting with the possibilities of the neural computing. TSB has been applying the system to forecasting the risk on insurance premiums, and is now seeing how it can be used to detect fraud. The computer can be trained to alert bank staff when an unusual transaction appears in a client’s account. Bankers also hope to train computers to tell them how much money load into their cash dispensers Not all banks, however, have had happy experiences with neural computing. One large bank reportedly lost millions of pounds before closing down its neural network in the problem with a technology still in its infancy is its unpredictability; it is difficult to know whether results will justify the expenditure.

4 Expert systems Expert systems are computer programs that attempt to replicate the performance of a human expert on some specialised reasoning task. Also called knowledge based systems, they are able to store and manipulate knowledge so that they can help a user to solve a problem or make a decision. The main features of an expert system are: It is limited to a specific domain (area of expertise) It is typically rule based It can reason with uncertain data (the user can respond “don’t know” to a question) It delivers advice It explains its reasoning to the user. An expert system has the following constituents: ‘the knowledge base’ that contains the facts and rules provided by a human expert Some means of using the knowledge (an ‘inference mechanism’ or ‘inference engine’) A means of communicating with the user (the ‘man-machine interface’ or ‘human computer interface’)

5 The knowledge base THE BASIC FEE FOR A 10 WEEK COURSE IS £25 FACT
The knowledge base will store knowledge in different forms, namely FACTS and RULES. For example: THE BASIC FEE FOR A 10 WEEK COURSE IS £25 FACT THE COURSE CODE FOR C PROGRAMMING IS EEC FACT IF STUDENT IS UNEMPLOYED THEN THE BASIC FEE IS WAIVED RULE IF STUDENT IS UNDER 18 THEN ALL FEES ARE WAIVED RULE ALL COURSES WITH CODES STARTING WITH ‘E’ CARRY AN EXTRA CHARGE OF £ RULE EEC5012 IS A 10 WEEK COURSE FACT Knowledge like this can be stored in a knowledge base, and the expert system should then be able to make deductions. If we supply the information that Jo Bloggs wishes to enrol for C Programming, the expert system should guide us through a series of relevant questions and deduce the fee to be charged. In practice there may be hundreds or thousands of facts and rules. When the program runs it dose not simply start at the first rule and run through them all; it makes deductions as it goes along, finding out what else it needs to know before providing a answer. The way in which it does this is called the ‘inference mechanism’. Part of the inference mechanism may be represented in rules – for example. IF AGE OVER 18 THEN CHECK EMPLOYMENT STATUS. Methods of reasoning fall into two categories: deduction and induction. Using deduction, we start with statements which are true in general, and make specific deductions from them e.g. given that All mammals suckle their young And whales are mammals We can deduce that Whales suckle their young. Using induction, we use facts like “All the swans I have ever seen are white” to induce that “All swans are white”. Of course sometimes, as in this case, these generalizations turn out not to be true. Some types of knowledge are rather indefinite and difficult to store in an expert system. For example: “This patient reminded me of one I saw a few months ago” “Sometimes coffee seems to keep me awake at night” “he is tall”

6 The man-machine interface
This describes the way in which the user interacts with the system by asking questions, supplying answers, requesting explanations, and so on. An inflexible interface will be like the traditional menu-drive programs where the user has to know what to enter and has little opportunity for error or variation. A better interface will be nearer to natural language and will let the user feel in control and well-informed throughout. Software that allows you to build an expert systems for some particular purpose is sometimes called an “Expert System Shell”, and the package Crystal is one example. This package allows you both to build the expert system and the use it to seek advice. FACILITIES OF AN EXPERT SYSTEM In summery, a good expert system should be able to Allow a user to specify the parameters for a problem Ask relevant questions and draw inferences from the replies Be capable of handling incomplete or imprecise information Allow the user to change parameters to explore ‘what if’ situations Make reasonable guesses or deductions Explain how it reaches its conclusions

7 Robotic and Embedded controls
There are many factories where robots are used on a production line. The jobs that the robots do are generally jobs which humans would find boring and repetitive, or jobs that may be dangerous. These jobs would previously have been done by humans, but they may have been re-trained for other jobs - or possibly have been made redundant. There will be some initial costs in purchasing the equipment and installing it, but the advantages of a robotic system would include.. robots work 24 hours a day - no need for breaks. robots do not need to be paid. robots work consistently - they do not get tired or make mistakes. Example : Computer-controlled robots may be found in car-making factories. The jobs they do may include.. welding or assembling parts paint spraying moving heavy parts around the factory. The robots will have been programmed to perform the jobs they do.

8 Stock Control The stock level of an item is the number of that item in store. When a shop sells items, it is sometimes important that the shop.. does not stock too many of an item e.g. The item might be perishable and those not sold will become unsellable. does not stock too few. A customer may want to buy one and there are none available. For these reasons shops set reorder levels and reorder quantities. When the number of items is reduced to the reorder level, then more of that item are ordered. The number of items ordered is determined by the reorder quantity. Stock Control is the administration of stock levels. A good stock control system will... keep track of exactly how many of each item are in stock. be able to say which items need re-ordering. analyse which items are selling well or needed most and which are not. All businesses which store items (in shops, warehouses etc) will need a stock control system. Some shops use barcodes and POS terminals for automatic stock control. A computer stores a master file with records of every item held in stock. One field would be the item's stock level. Every time an item is bought, the barcode is scanned and the computer will deduct 1 from the stock level for that item. The computer will know exactly how many of that item are in stock. A similar system would operate in a warehouse. Each item removed would be logged and the stock level automatically adjusted. This would be an example of a real-time system. Data is processed s soon as it is received and the system is always up-to-date.

9 Order Processing Customers may buy goods from a business by sending an order - which will have details of which items they want to buy and how many. Orders may be received... ...through the post on order forms. These will need to be entered onto the computer as records on the orders file. Customers send orders by or over the Internet. These orders would be saved in the orders file. The orders file would have fields with information about ... the date of the order customer details item details and quantities money owing or received from the customer. Appropriate data validation will take place when the orders are entered. When the goods are dispatched, an invoice is sent requesting the amount of money due for the order. The customer may then pay by cherub. Online orders are usually paid for using credit (or debit) cards. If goods are paid for online over the Internet, there would need to be a secure system in place to avoid problems with credit card details being stolen. When an order is processed.... stock levels are adjusted for the items sent. financial information is stored and analysed. Who owes what and how much has been received etc statistical information is updated - numbers of sales, best selling products etc...

10 Expert systems ...has a large database of knowledge.
...allows the database to be interrogated. ...has a set of rules (inference engine) for making deductions. An expert system is a computer system which simulates the knowledge and expertise of a human expert. For example, in Medicine, expert systems are being used for disease diagnosis. The patient's details and symptoms are input, and the system outputs probable diagnoses, recommended treatments or drugs which may be prescribed.  Expert systems are not really replacing doctors but are being used to help them. There are ethical and legal reasons for this - if a computerised diagnosis is wrong, who do you sue? Some patients would feel happier typing medical information into a computer than discussing it with a human doctor...but others would prefer the 'human' touch. The advantages of an expert system over a doctor are... ...a large database of knowledge can be added to and kept up-to-date - it can store more knowledge than a person. ...the system cannot 'forget' or get facts wrong. survives forever. There is no loss of knowledge as there is when a doctor retires. ...the computer can access specialist knowledge that a doctor may not have.   An expert system would be programmed using an AI (Artificial Intelligence) language such as PROLOG.

11 Booking Systems It is now possible to make bookings on-line for holidays, trains, planes, hotel rooms, theatre performances...and many others. A travel agent for example, may have computers in all its branches directly connected to a central computer where a database of all bookings is stored. This is an example of a multi-access system.   When a booking is made, the customer will need to provide input details  (name, date, place, number of people etc).  These details may be entered ... at a computer terminal in a multi-access system. on a form on an Internet web page. by transcribing them from a paper booking form. by typing them in when in telephone communication with the customer. This form (on an Internet web page) is used for collecting details of a passenger's booking on the Euro tunnel. These details are then used as input data when the booking is made. This data is validated to check if the details are sensible. The computer will check to see if the booking is available, and, if it is, the booking is made and it will then store the booking details in the database. Documents will need to be output to give to the customer, confirming the booking and giving details about it. As soon as a customer makes a booking it has to be processed immediately, so that no other customer can make the same booking. This means it is a real-time (transaction processing) system. It is essential that no data is lost, so the database will have to be regularly backed up - possibly using a tape streamer. If payments for the booking are required, then these can generally be done on-line using a Credit card or a Debit card. If details of these are transmitted over the Internet, the website must be secure so that this information cannot be stolen.

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