Expected questions in Artificial Intelligence

1. EXPECTED QUESTIONS
UNIT-1
PART-A
1. What is ridge? MAY2016
2. Howmuch knowledge would be required by a perfect program for a problem of playing
chess? Assume that unlimited computing power is available. MAY2016
3. Define heuristics.Why are heuristics crucial for the efficient design ofan expert system?
4. List the criteria to measure the performance ofsearch strategies.
5. What is production systems
6. What is AI technique
7. What are the steps to be considered to solve a problem?
8. What are the three classes ofproblem
9. What are the problems faced by hill-climbing search
10. What is Constraint satisfaction?
Part-B
1. (i) Explain the heuristic functions with examples. (6) MAY 2016
(ii) Write the algorithm for generate and test and simple hill climbing. (10) MAY 2016
2. Solve the given problem. Describe the operators involved in it.
Consider a water jug problem: You have given two jugs, a 4-gallon one and a 3-gallon
one. Neither have any measuring markers on it. There is a pump that can be used to fill
the jugs with water. How can you get exactly 2 gallons of water in to the 4-gallon jug?
Explicit Assumptions: A jug can be filled from a pump, water can be poured out of a jug
on to the ground, water can be poured from one jug to another and that there are no
other measuring devices available. MAY 2016
3. (i) Describe a state space in which iterative deepening search performs much worse
than depth-first search.
(ii) Prove that the breadth first search is a special case of uniform cost search.
4. Explain the Control strategies in detail.
5. Explain how different problem characteristics are analyzed in detail.
6. Explain production systems and discuss the major issues in the design of search
programs.
7. What is heuristic search technique? Explain Hill climbing in detail.
8. Explain Best-first search algorithm in detail.
9. Write algorithm for the following:
i. Generate-and-test
ii. A* Algorithm
iii. Agenda-driven search
iv. Means-end analysis
10. Explain problem-reduction algorithm in detail.
i. AND–OR Graph Search:
ii. AO* algorithm
11. Explain AO* algorithm with a suitable example. State the limitations in the algorithm.
AO* algorithm:
12. Explain the constraint satisfaction procedure to solve the crypt arithmetic problem.
C R O S S
+ R O A D S
D A N G E R (NOV/DEC 2011)

2. Unit-2
1. What is alpha-beta pruning? MAY2016
2. For a given sentence “All Pompieans were Romans”.Write a well formed formula in
predicate logic. MAY2016
3. What are the levels of knowledge representation?
4. What are forward and backward representation mappings?
5. Represent the following sentence in predicate form “All the children likes sweets”.
(NOV/DEC 2012)
x Likes (x,sweets)
6. Define resolution..
7. State Herbrand’s theorem.
8. State the use of unification. (MAY/JUNE 2012)
9. What is MINIMAX Search Procedure?
10. Give some examples of structured representation of knowledge and define them.
PART-B
1. Convert the following well formed formula into clause form with sequence ofsteps:
∀x[Roman(x)  Know(x, Marcus)][hate(x,Caesar) (∀y:
z:hate(y,z)thinkcrazy(x,y))] MAY2016
2. (i)Write the resolution procedure for prepositional logic(8) MAY 2016
(ii) Explain the iterative deepening algorithm. (8). MAY 2016
3. Explain in detail the approaches to Knowledge Representation.
4. Explain the various issues in knowledge Representation in detail.
5. Differentiate predicate and propositional logic. Explain predicate logic with suitable
illustrations.
6. Explain the unification algorithm used for reasoning under predicate logic with an
example. (APRIL/MAY 2011)
7. Consider the following facts
a. Team India
b. Team Australia
c. Final match between India and Australia
d. India scored 350 runs,Australia scored 350 runs, India lost 5 wickets, Australia lost
7 wickets.
e. The team which scored the maximum runs wins.
f. If the scores are same the team which lost minimum wickets wins the match.
Represent the facts in predicate, convert to clause form and prove by resolution “India
wins the match”. (NOV/DEC 2011)
8. Consider the following facts and represent them in predicate form:
F1. There are 500 employees in ABC company.
F2. Employees earning more than Rs. 5000 pay tax.
F3. John is a manager in ABC company.
F4. Manager earns Rs. 10,000.
Convert the facts in predicate form to clauses and then prove by resolution: “John pays
tax”. (NOV/DEC 2012)
9. Explain with an example concept of resolution. (NOV/DEC 2012)
10. Explain MINIMAX Search Procedure algorithm with suitable illustration.
11. Explain alpha-beta pruning in detail along with example.
12. Explain various structured knowledge representations in detail.

3. UNIT-3
1. What is Bayesian Networks? MAY 2016
2. Write the properties offuzzy sets. MAY2016
3. What factors determine the selection of forward or backward reasoning approach for
an AI problem? (APRIL/MAY 2011)
4. Define Dempster-Shafer theory
5. Define Certainty factors.
6. Define Bayes’ rule
7. Define Forward chaining.
8. Define Backward chaining
9. Write briefly about fuzzy set theory
10. What are the various kinds ofknowledge
Part-b
1. (i) Briefly explain how reasoning is done using fuzzy logic. (6) MAY 2016
(ii) Explain Dempster-Shafer theory. (10) MAY 2016
2. What is forward chaining and how does it works? Explain the forward chaining
algorithm with example. (16) MAY 2016
3. Describe the various issues in knowledge representation.
4. How does an inference engine work in a frame based system?
5. Explain the need of fuzzy set and fuzzy logic with example. (MAY/JUNE 2012 &
NOV/DEC 2013)
6. Explain the method of performing exact inference in Bayesian networks. (NOV/DEC
2012)
7. Explain in detail about forward and backward chaining with suitable example.
8. Explain knowledge representation in detail with example.
9. Explain Rule based system with example.
10. Write notes on:
iii) Certainty factors
UNIT-IV
1. 1.What is rote learning?
2. Briefframe problem. MAY2016
3. 3.Define STRIPES
4. Mention the components of Planning system.
5. What are the basic operations in the Blocks world
6. Define Machine learning.
7. What are the various forms of learning
8. Define concept- learning
9. What is Goal Stack
10. Mention the advantages of Machine Learning.
Part-b
1. (i) Describe the components of a planning system. (10) MAY 2016
2. (ii) What is ID3? Write the drawbacks of ID3? (6) MAY 2016
3. Describe the hierarchical planning method with example. (8) MAY 2016

4. 4. (ii) Describe the learning with Macro operators. (8) MAY 2016
5. Explain STRIPES mechanism with example.
6. Explain the concept of planning with the Block world example.
7. Discuss simple planning using a Goal Stack.
8. Write briefly the concept of Learning.
9. Explain Machine learning and Adaptive learning with example.
10. Solve the blocks world problem using strips. How does it act as a planning system?
UNIT-V
Part-A
1. What is meta knowledge? Howmeta knowledge is represented in rule-based expert
system? MAY2016
2. Write any four earliest expert systems. MAY2016
3. Define Expert systems.
4. What are the limitations of Expert systems
5. What is a shell
a. Mention the 3 major components of an Expert system
6. What are the advantages of Expert systems
7. Mention applications of Expert system.
8. Define MYCIN
9. Define DART
10. 17. What are the classifications of expert systems?
Part- B
1. (i) Explain about the knowledge acquisition. (10) MAY 2016
(ii) Write the characteristic features of Expert system. (6) MAY 2016
2. (i) Explain the basic components of an expert system. (10) MAY 2016
(ii) Write any six applications of expert systems. (6) MAY 2016
3. What are Expert systems? Explain in detail.
4. Elaborately explain the process of knowledge acquisition.
5. i) Explain the various stages of Expert system development.
ii) Explain heuristics with a example
6. Draw the schematic diagram ofan expert system. Explain all the relevant components.
7. i) Explain the components of expert systems with a neat diagram.
ii) Discuss the features of Expert systems
8. Discuss the advantages and limitations of expert systems.
9. i) Explain briefly about Meta knowledge
ii) Explain the role of expert system
10. Write short notes on:
a. MYCIN and its applications
b. DART and its applications
11. Write notes on:
i) Expert system shell
ii) Limitations of Expert systems
12. Explain the pitfalls in selecting an expert system.