UNIVERSITY OF SURREY

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1 UNIVERSITY OF SURREY B.Sc. Undergraduate Programmes in Computing B.Sc. Undergraduate Programmes in Mathematical Studies Level HE3 Examination MODULE CS364 Artificial Intelligence Time allowed: 2 hours Spring Semester 2003 Attempt THREE Questions If any candidate attempts more than THREE questions, only the best THREE solutions will be taken into account. SEE NEXT PAGE 1

2 1. (a) Describe the four major tasks performed by a knowledge engineer in the process of knowledge acquisition. (b) List five potential sources of knowledge for a knowledge engineer and state where in the knowledge acquisition process (early, middle or late) each source might be applicable. [5 marks] (c) The following is a short extract from an interview between a Knowledge Engineer (KE) and an expert diagnostician (E) concerned with discovering the major diagnostic concepts in respiratory medicine, and how the concepts are related. KE: Can you give me some idea about the major types of respiratory diseases or illnesses? E: Well, the major divisions would be upper and lower respiratory tract diseases. KE: Can you give me some examples of lower respiratory tract diseases? E: Well, there s pneumonia, uh, COAD... KE: What s COAD? E: That stands for chronic obstructive airways disease. Things like bronchitis, emphysema... KE: Ah... OK, bronchitis and emphysema are kinds of COAD, right? E: That s right, they re both kinds of COAD. KE: And some examples of pneumonia? Can that be further subdivided? E: Well sure. There s Legionnaire s disease. There s pneumocystis pneumonia. There are several types actually. KE: Legionnaire s disease is a kind of pneumonia is it? I never knew that. I thought it was probably something that you got from drinking bad water or something. E: No, it s a pneumonia. A bacterial pneumonia, in fact. KE: Bacterial pneumonia? Is pneumocystis a bacterial pneumonia? E: No, that s a fungal pneumonia. That s caused by... KE: Right, so there s bacterial and fungal pneumonias. Are there any other types? QUESTION 1 CONTINUED : SEE NEXT PAGE 2

3 E: Non-bacterial pneumonias. That s the three major types. Uh, and aspiration pneumonia, that s separate. KE: Okay. Let s see if this is what you mean. Four subdivisions of pneumonia, Legionnaire s disease is a bacterial one, and pneumocystis is fungal, right? (i) List 12 types of disease mentioned in the interview. [4 marks] (ii) Draw a hierarchy diagram that shows the relationships between the various types of lower respiratory tract diseases discussed above. [9 marks] SEE NEXT PAGE 3

4 2. (a) It is claimed that a semantic network representation has problems of logical and heuristic inadequacy. Explain what is meant by logical inadequacy and heuristic inadequacy. (b) For each of the following sentences suggest which knowledge representation formalism you would consider most appropriate and explain why. (i) Tony followed the loud man. (ii) All the drivers thanked the marshal. (iii) Michael drove his car from Hockenheim to the Nurburgring. (iv) The party is at 123 Acacia Avenue and the hosts will be Tony and George. [8 marks] (c) The following three press reports describe an earthquake, a flood and a fire. An earthquake measuring 8 on the Richter scale hit Guildford on the 15th November killing 15 people and causing 1,000,000 in damage. The earthquake was caused by a shift in the Blair fault. The river Mole in Guildford flooded yesterday, the 19th November. The flood reached a height of 20 meters and 5 people were drowned. The flood covered an area of 1 square mile and is estimated to have caused 750,000 worth of damage. Three fire engines and eighteen firemen attended a blaze at the University of Surrey last Sunday, 24th November. Fortunately the fire occurred late at night in an unoccupied building and there were no casualties however authorities put the damage at 300,000. Construct a frames representation of these disasters, making sure that you use the inheritance properties of the frame representation to the full. [10 marks] SEE NEXT PAGE 4

5 3. The operation of a fuzzy expert system depends on the execution of four major tasks: Fuzzification, Inference, Composition, and Defuzzification. (a) Describe each of the four major tasks in your own words. [4 marks] (b) The Parsimonious Phone Company sells mobile phones using the following rules: IF is Excellent OR Debts are Small THEN is Low IF is Good AND Debts are Large THEN is Normal IF is Poor THEN is High Excellent The membership functions for the linguistic variables, Debts, and are given as in 90; Excellent x 120; Good 50 & x 100; Good x = 75; Poor 60; Poor x 10; Small Debt 50; Small Debt x 10; L arg e Debt 15; L arg e Debt x 60; Low 40%; Low x 20%; Medium 20% & x 80%; Medium 40% x 60%; High 60%; High x 80%; (i) Jim has applied for a phone: his salary is 140K and his debts amount to 60K. Use the rule base to compute the risk associated with Jim using the mean of maxima in the Defuzzification task. [10 marks] QUESTION 3 CONTINUED : SEE NEXT PAGE 5

6 (ii) Show your computations clearly for each of the four tasks involved in finding the level of risk associated with Jim. (iii) Compute the risk associated with Jim using the centre of area computation in the Defuzzification task. (iv) Comment on any difference between the results of the computations in (ii) and (iii) above. SEE NEXT PAGE 6

7 4. Martin has run successful Formula 1 motor racing team for a number of years, and has a reputation for promoting young drivers that go on to win championships. This year Martin has to find a suitable replacement driver for one of his cars, but wants to pick the driver who has the best chance of being a champion in the future. To help, he is trying to generate a way of classifying potential champions by using the following career data for his past signings: Name Competed in F3000 Won F3000 Championship F1 Champion 1 Yan Y N Y 2 Jean N N N 3 Ralf Y N Y 4 Rosa N N N 5 Sally Y N Y 6 Eddie N Y Y 7 Kun N Y Y 8 Mark Y Y Y (a) Martin is considering using Decision Tree Learning to produce a system to classify potential drivers. Two different decision trees can be drawn from the data in the table above. The ID3 algorithm is a popular algorithm for generating decision trees by selecting the best attributes for each node. Briefly describe how a decision tree can be constructed using the ID3 algorithm. [6 marks] (b) Given an attribute a (for example Competed in F3000 ), which has a value v (either Y or N ), the entropy for the c different classifications (F1 Champion: Y or N ) is defined by: E c ( a = v) = i= 1 p i log p i Furthermore, given a set of training examples T (the values in the table above), and a subset of these T j that have the attribute a equal to value v, the information gain is defined by: Gain v j ( T, a) = E( T ) E( T j ) j= 1 T T 2 QUESTION 4 CONTINUED : SEE NEXT PAGE 7

8 (i) Calculate the missing entropy and information gain values from the following table (marked by an * ). [4 marks] p i Pr( " F1Champion = Y" ) p i Pr( " F1Champion = N" ) Entropy ( a v) Information Gain ( T a) Attributes All Compete in F3000 Won F3000 Championship Y N Y N = = E = * Gain, * (ii) Based upon this information, which attribute would you choose as the root of the decision tree? Explain the reason for this choice. [4 marks] (c) Martin has decided to use additional data he has available to help in classifying new drivers, using the decision tree technique explored above. Briefly describe two problems Martin may encounter in the learning process for constructing a decision tree, and the ways in which these problems may be overcome. [6 marks] INTERNAL EXAMINERS: PROF K. AHMAD/MR C. HANDY/MR M. CASEY EXTERNAL EXAMINER: PROF Y. WILKS 8