Course Title: Artificial Intelligence
Course Code: PCC-CSE-304-G
Semester: B.Tech. 6th Semester (CSE)
May 2024
Question 1 (15 × 1 = 15 marks)
- (a) Define Turing Test.
- (b) What are the limitations of Depth-first search?
- (c) Why hill climbing algorithm is called greedy local search?
- (d) What are the knowledge representation issues?
- (e) What is the limitation of propositional logic?
- (f) How does an inference engine work in rule-based system?
- (g) What is the difference between prior and posterior probability?
- (h) What is the difference between Bayesian and Dempster-Shafer theory?
- (i) What are the standard quantifiers of First-order logic?
- (j) What is the difference between search vs planning?
- (k) Which are the components of the partial-order planning?
- (l) What is an Activation Function?
- (m) Differentiate between artificial neural network and biological neural network?
- (n) What are the limitations of expert systems in AI?
- (o) Define explanation-based learning.
Unit-I
Question 2
- (a) What is the difference between A* and AO* algorithms? (5 marks)
- (b) Consider a water jug problem. You are given 2 jugs; a 3-gallon jug and a 4-gallon jug. Neither has any measuring marks on it. There is a pump that can be used to fill the jugs with water. How can you get exactly 2-gallon of water into a 4-gallon jug? State the production rules for the water jug problem. (10 marks)
Question 3
- (a) Define Encoding in Genetic algorithm. Describe the different encoding methods. (10 marks)
- (b) Write short notes on:
- (i) Roulette Wheel selection
- (ii) Tournament selection (5 marks)
Unit-II
Question 4
- (a) Convert the following statements in Predicate Logic: (10 marks)
- Not all students like both AI and DS.
- Everyone likes someone.
- Someone ate everything.
- Some girls are intelligent.
- Everyone likes rain.
- Jill eats almonds and is still alive.
- Mary eats everything John eats.
- Anything anyone eats and is not killed by is food.
- Mangoes are food.
- Bill likes all kinds of food.
- (b) How are frames used for knowledge representation? Explain using example. (5 marks)
Question 5
- (a) Draw the semantic network representing the following knowledge: Every vehicle is a physical object. Every car is a vehicle. Every car has four wheels. The electrical system is a part of car. The battery is a part of the electrical system. Pollution system is a part of every vehicle. The vehicle is used in transportation. Honda City is a car. (8 marks)
(b) Differentiate between forward and backward reasoning. (7 marks)
Unit-III
Question 6
- What is Dempster-Shafer's theory? Explain with a suitable example. (15 marks)
Question 7
- Explain partial-order planning with a suitable example. (15 marks)
Unit-IV
Question 8
- Why do neural networks need an activation function? Classify different types of neural network activation functions. (15 marks)
Question 9
- Explain the architecture of an Expert System. Give its three application areas. (15 marks)
May 2023
Question 1 (6 × 2.5 = 15 marks)
- (a) Uninformed Search
- (b) Genetic Algorithm
- (c) Dempster-Shafer Theory
- (d) Explanation Based Learning
- (e) Expert System
- (f) Identification Trees
Unit-I
Question 2
- (a) What is Artificial Intelligence? State examples of AI problems. (8 marks)
- (b) Differentiate the DFS and BFS with merits and demerits. (7 marks)
Question 3
- (a) Explain the Best-First-Search Procedure with example. (8 marks)
- (b) Explain algorithm A* with example. *(7 marks)*
Unit-II
Question 4
- Explain in detail Knowledge Representation Techniques and schemes. (15 marks)
Question 5
- State various issues in knowledge representation in detail. (15 marks)
Unit-III
Question 6
- Explain Probability and Bayes Theorem with example. (15 marks)
Question 7
- What is Partial-order Planning? Explain in detail. (15 marks)
Unit-IV
Question 8
- What are the current trends in AI? Elaborate. (15 marks)
Question 9
- Explain the following types of learning: (15 marks)
- (a) Learning by Induction
- (b) Rote Learning
- (c) Symbol Based Learning
July 2022
Question 1 (6 × 2.5 = 15 marks)
- (a) History of AI
- (b) Ant Colony Optimization
- (c) Bayesian Reasoning
- (d) Transformational Analogy
- (e) Neural Networks
- (f) Informed Search
UNIT-I
Question 2 (15)
- What do you mean by Game Playing: Min-Max Algorithm and Alpha-Beta Pruning? Explain in detail.
Question 3 (15)
- (a) Explain A* algorithm.
- (b) What is Hill Climbing? Explain simple Hill Climbing.
UNIT-II
Question 4 (15)
- Describe different Approaches to Knowledge Representation.
Question 5 (15)
- Explain Rule Based System with example.
UNIT-III
Question 6 (15)
- Explain in detail Dempster-Shafer Theory.
Question 7 (15)
- What is Probability Theory in terms of Reasoning under Uncertainty? Elaborate with example.
UNIT-IV
Question 8 (15) Explain in detail Expert systems.
Question 9 (15) Demonstrate a discussion of AI, its current trends, limitations and applications.
July 2021
Question 1 (5 × 3 = 15 marks)
- (a) Differentiate between informed and uninformed search.
- (b) Write a short note on Semantic Network.
- (c) What do you mean by term Heuristics?
- (d) Explain the term Non-monotonic reasoning.
- (e) Write a short note on genetic algorithms.
UNIT-I
Question 2
- (a) Define term Artificial Intelligence. What are applications of AI in various fields? (7 marks)
- (b) Explain Hill Climbing strategy with example. What are the problems faced while applying this strategy? (8 marks)
Question 3
- (a) What do you mean by Game playing in AI? (7 marks)
- (b) Explain Alpha-Beta pruning with example. What is the need of pruning? (8 marks)
Unit-II
Question 4
- (a) Differentiate between propositional logic and predicate logic. (8 marks)
- (b) What do you mean by Skolemization? (7 marks)
Question 5
- Explain the various ways of knowledge representation in AI (15 marks)
Unit-III
Question 6
- (a) Explain how uncertainty is managed in AI. (5 marks)
- (b) Explain Dempster shafer theory with the help of example. (10 marks)
Question 7
- (a) Discuss partial-order plan with example. (7)
- (b) How do we represent states, goals and actions in planning? Explain with example. (8)
Unit-IV
Question 8
- What is an Expert System? Explain its architecture in detail. Also, write its applications in the various domains. (15 marks)
Question 9
- (a) Explain ANN with its architecture. How artificial Neural networks are different from biological neural networks? (8 marks)
- (b) Explain ANN applications in the various fields. (7 marks)