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Introduction To Artificial Intelligence Question Paper

Introduction To Artificial Intelligence

Course:Bbit 221

Institution: Kenya Methodist University question papers

Exam Year:2008

KENYA METHODIST UNIVERSITY

END OF FIRST TRIMESTER 2008 EXAMINATION

FACULTY : BUSINESS AND MANAGEMENT STUDIES
DEPARTMENT : BUSINESS ADMINISTRATION
COURSE CODE : BBIT 221
COURSE TITLE : INTRODUCTION TO ARTIFICIAL INTELLIGENCE
TIME : 3 HOURS

INSTRUCTIONS
• Answer ONE question from EACH section.

SECTION A [COMPULSARY]
Question 1[30 Marks]
a) Describe the following
i. Artificial Intelligence
ii. Rational Agent
iii. Nomonotonic reasoning
iv. Turing test
v. Modus Ponens [5 Marks]
b) Give three human traits attributed to Intelligence. [3 Marks]
c) Explain any two characteristics of agents. [4 Marks]
d) Name two early successes of AI programs in computing industry.
[2 Marks]
e) Translate the following into predicate calculus.
i. Every gardener who lives in a city likes the sun. [2 Marks]
ii. All cats like fish, cats eat everything they like. Ziggy is a cat.
[2 Marks]
f) Describe three knowledge representation techniques highlighting the advantages of each technique. [6 Marks]
g) Using a well labeled diagram describe the structure of an expert system.
[6 Marks]
SECTION B (Answer either Question 2 OR Question 3)
Question 2 [20 Marks]
a) We may know that 50%of people with measles have spots. We may also know that: The only diseases that cause spots are measles, chickenpox and lassa fever.
60%of people with chickenpox have spots.
80%of people with lassa fever have spots.
There is a 1%chance of someone in a given population having measles (given no evidence for or against).
There is a 1%chance of them having chickenpox.
There is a 0.05%chance of them having lassa fever.
What is the probability that people have measles if they have spots?
[3 Marks]

b) Shown below is a graph representing a map navigation problem:

The path cost is shown by the number on the links; the heuristic evaluation shown by the number in the boxes.
Assume that during the search:
• S is the start node and G is the goal state
• When placing the nodes on the queue use alphabetical ordering to break the ties
• Assume we never generate child nodes that appears are ancestors of the current node in the search tree.
What is the order that the following search algorithms will expand the nodes?
i. Breadth First Search
ii. Iterative Deepening Search
iii. Hill Climbing search
iv. A* Search
[8 Marks]
c) If it’s raining out then Ann puts the top up on her convertible. Ann did put the top up on her convertible. Using logical inference rules answer the question: “Is it raining?”
[3 Marks]
d) Give two applications of real world systems that you consider to be examples of artificial intelligence systems. Briefly describe the systems and justify why you belief they fall in this category. [6 Marks]
Question 3 [20 Marks]
a) Define
i. Heuristic evaluation function
ii. Problem space
iii. Path cost [3 Marks]
b) Ann is a program at Techno Computers and is in charge of writing a program to control their assembly line machines. They have a robotic arm which must solder chips onto a circuit board at the points shown below.
The arm starts in the left corner and it must visit every point on the circuit board and return to its starting point. Help Ann minimize the total distance the arm must travel by formulating this problem as optimization problem.

i. Develop state representation for this optimization problem
[2 Marks]
ii. Which search operator can be used to change the position of any two elements? [2 Marks]
iii. Recommend two search algorithms for Ann to use to find the best route for the arm to take. Justify your recommendation. [4 Marks]
c) Discuss by giving 2 salient points the significance of artificial intelligence in commerce. [5 Marks]
d) Contrast the following:
i. Prior Belief and Posterior Belief
ii. Degree of belief and degree of truth [4 Marks]

SECTION C (Answer either Question 4 OR Question 5)
Question 4 [20 Marks]

a) Explain briefly what an expert system is. Give an example of an application for an ES. [3 Marks]

b) What are the main conflicts that can arise in an expert system when the number of rules becomes large? How can those conflicts be solved?
[4 Marks]
c) Differentiate between deductive and abductive reasoning [2 Marks]

d) Discuss three sources of uncertainty in AI problems [6 Marks]

e) Using an example describe how Fuzzy Logic deals with uncertainty.
[5 Marks]
Question 5[20 Marks]

a) Give the type of agents suited for the following domain applications. Give reasons for your answer:
i. Medical diagnosis system.
ii. English Tutoring system. [4 Marks]
b) Using a well illustrated diagram, describe the structure of a learning agent.
[5 Marks]
c) What is machine learning? Describe the following in relation to machine learning
i. Inductive learning
ii. Artificial Neural Network [5 Marks]
d) Consider the example here below:
An ES has the following facts and rules.
R1: IF one has at least 1 million shillings to invest AND has basic knowledge of running businesses THEN he should invest in securities.
R2: IF the persons annual income is 50 million AND has basic knowledge of running businesses THEN he should invest in stocks.
R3: IF a person is younger than 30 but older than 22 THEN he should invest in stocks.
R4: IF a person is younger than 30 but older than 22 THEN he has basic knowledge of running businesses.
R5: IF a person is wants to invest in stocks THEN he should invest KenGen shares.
FACTS: Person has at least 1 million shillings to invest.
Person is 25 years old
GOAL: Does he/she invest with KenGen shares?
Answer the question using forward and backward chaining approaches. [6 Marks]

Introduction To Artificial Intelligence Question Paper

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