Past Guess Paper of Artificial Intelligence.

Past Guess Paper of Artificial Intelligence.

Guess Paper 1 : Artificial Intelligence Past Papers

University Name – Confidential

NOTE: Q.1 is compulsory, attempt any four questions from the remaining. All questions carry equal marks. Phones and other Electronic Gadgets are not allowed.

Time Allowed: 3 hours

Examination:   Final, Fall – 2020

Total Marks:    70, Passing Marks (35)

Q.1 Short answer or Fill in the Blanks [14 Marks]

a. What is the purpose of search algorithm in AI.
b. Which search strategy is also called as blind search?_________________.
c. __________ symbol is used to show if a predicate is true for some of the members of a set.
d. A _____________________ is a computer program that reasons and uses a knowledge base to solve complex problems
e. Define inference rule.
f. _______________ explores the construction and study of algorithms that can learn from and make predictions on data.
g. ______________ is computerized advice-giver, that is capable of reasoning but which is usually confined to a rather narrow field of knowledge.

Q.2 Describe major areas and applications of Artificial Intelligence in computer science. (14)
Q.3 (a) Define propositional logic. What are major operations and symbols in propositional?
(b) Let we have two propositions A= Ali is boy, B = Mary is a Girl. Write these sentences using propositional logic
I. Ali is boy and mary is a girl II. Ali is boy and mary is not a girl
III. Ali is not a boy or mary is a girl IV. If Ali is boy then mary is a girl

Q.4. Write a detailed note on search in problem solving. Name and define major types of search algorithms.
(14)
Q.5. Write a note on Prolog language. Describe major components of Prolog (Data Types, Lists, Functions
and Statements). Provide an example program. (14)

Q.6 (a) Write a note on architecture of Expert systems.
(b) Discuss rule based expert system with example (7+7)

Q.7 (a) Explain Machine learning and its types.
(b) Describe rule based learning with example. (14)
Q.8. Write short notes on any TWO of the following.
(a) Computer Aided Instruction (07)
(b) Robotics (07)
(c) Neural Networks (07)

Guess Paper 2 : Artificial Intelligence Past Papers

University Name – Confidential

NOTE: Q.1 is compulsory, attempt any four questions from the remaining. All questions carry equal marks. Phones and other Electronic Gadgets are not allowed.

Time Allowed: 3 hours

Examination:   Final, Spring – 2020

Total Marks:    70, Passing Marks (35)

Q.1 Short answer or Fill in the Blanks [14 Marks]

Q.1 Fill in the blanks [14 Marks]

i. What is the purpose of search algorithm in AI.
ii. What are components of knowledge based system.
iii. Define inference rule.
iv. Describe the situation when depth first search is better.
v. _______________ explores the construction and study of algorithms that can learn from and make predictions on data
vi. __________ symbol is used to show if a predicate is true for some of the members of a set.
vii. A _____________________ is a computer program that reasons and uses a knowledge base to solve complex problems

Q.2. (a) Write a detailed note on Artificial Intelligence.
(b) Describe major areas and applications in Artificial Intelligence. (7+7)
Q.3 (a) Describe propositional logic with example.
b) Let we have these predicates B(x,y)= Brothers, S= Siblings, L (x,y)= Love. Write these sentences using predicate logic
i. Ali and Umar are brothers
ii. Brothers are siblings
iii. Everybody loves somebody
vi. There is someone who is loved by everyone. (7+7)

Q.4. (a) Compare A* search with Hill climbing and Min Max Search.
(b) Differentiate depth first search and breadth first search with example. (10+4)

Q.5. Write a note on LISP language. Describe major components of Lisp (Data Types, Lists, Functions and Statements). Write a LISP function which will return number which is greater from given two numbers (14)

Q.6 (a) Write a note on architecture of Expert systems.
(b) Discuss rule based knowledge based system with example (7+7)

Q.7. Write short notes on any TWO of the following.
(a) Natural Language Processing (07)
(b) Robotics (07)
(c) Machine Learning. (07)

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