Artificial Intelligence - R23 - Model Paper 1

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MODEL QUESTION PAPER – ARTIFICIAL INTELLIGENCE

(B.Tech – III Year I Sem, JNTUK R23 Syllabus)
Time: 3 Hours                                                                                                                Max. Marks: 70

SECTION – I (10 × 5 = 50 Marks)

(Answer ALL questions. Each question has (a) & (b).)

Unit – I (Introduction)

1. (a) Explain the structure of an intelligent agent with neat sketch. (5M)
(b) What is rationality in AI? Explain with examples. (5M) 

(or)

2. (a) Differentiate between agents and environments. (5M)
(b) What are the foundations of Artificial Intelligence? (5M)

Unit – II (Searching)

3. (a) Explain Breadth-First Search (BFS) with example. (5M)
(b) Write short notes on Depth-First Search (DFS). (5M)

(or)

4. (a) Explain Hill Climbing algorithm with its merits and demerits. (5M)
(b) Write about Minimax algorithm with an example. (5M)

Unit – III (Knowledge Representation)

5. (a) Differentiate between propositional logic and predicate logic. (5M)
(b) Explain semantic networks with inheritance. (5M)

(or)

6. (a) Explain rules-based deduction system with example. (5M)
(b) Write short notes on reasoning under uncertainty using Bayes theorem. (5M)

Unit – IV (Logic & Learning)

7. (a) Explain forward chaining with a neat example. (5M)
(b) Write a short note on unification in first-order logic. (5M)

(or)

8. (a) Explain decision tree learning with a simple example. (5M)
(b) What is reinforcement learning? Explain with example. (5M)

Unit – V (Expert Systems)

9. (a) Write a short note on the architecture of expert systems. (5M)
(b) Explain MYCIN expert system. (5M)

(or)

10. (a) Explain the role of knowledge base and inference engine in expert systems. (5M)
(b) Write a short note on XCON expert system. (5M)

SECTION – II (10 × 2 = 20 Marks)

(Answer ALL questions. Each carries 2 marks)

11. Define Artificial Intelligence.
12. Write two real-world applications of AI.
13. What is a heuristic function?
14. Define adversarial search.
15. What is a frame in knowledge representation?
16. Define semantic network.
17. What is resolution in logic?
18. Define inductive learning.
19. What is meta-knowledge in expert systems?
20. Write two limitations of expert systems.

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