Course: B.Tech (Semester V) Subject Code: KAI-501
Subject Name: Artificial Intelligence Time: 3 Hours
Total Marks: 100
Section A — Short Answer Questions (2 × 10 = 20 Marks)
Answer all questions briefly:
Difference between Artificial Intelligence, Machine Learning, and Deep Learning.
Relationship between task environments and rational agents.
Define Backtracking Search.
Define Constraint Satisfaction Problems (CSP).
Difference between Forward Chaining and Backward Chaining.
Apply upper ontology concepts with an example.
Define characteristics of Information Retrieval.
Define Argumentation among Multi-Agent Systems.
Differentiate between Machine Translation and Speech Recognition.
Define Skeletonization method and Voronoi graph.
Section B — Descriptive Questions (10 × 3 = 30 Marks)
Attempt any three:
Define four categories of Intelligent Systems.
Validate a logical statement using reasoning:
“If price falls then sales increase. If sales increase then John makes money. But John doesn’t make money. Therefore, price does not fall.”
Convert the given sentences into Predicate Logic, Clausal Form, and perform Resolution for the goal: Scrooge is not a child.
Draw the Abstract Model for Interoperating Software Agents.
Define Artificial Intelligence and list the six disciplines needed for an intelligent system to pass the Turing Test.
Section C — Long Answer Questions (10 × 5 = 50 Marks)
Question 3
(a) Define AI and the six disciplines for the Turing Test.
or
(b) Explain different approaches to solving AI problems.
Question 4
(a) Demonstrate Alpha-Beta Pruning Algorithm with example.
or
(b) Define Heuristic Search and explain Greedy Best-First Search with example.
Question 5
(a) Solve an 8-Puzzle Problem using A* algorithm.
or
(b) Represent the Monkey-Banana Problem in Predicate Logic.
Question 6
(a) Explain Trust and Reputation in Multi-Agent Systems with examples.
or
(b) Define Intelligent Agent and explain four classes of agent architectures.
Question 7
(a) Describe the Role of Computer Vision in Artificial Intelligence.
or
(b) Define Pattern Recognition and explain its design principles with examples.
