2025 question paper

Artificial intelligence

28 questions

  1. Q1a. The Turing Test was proposed by (i) John McCarthy (ii) Alan Turing (iii) Marvin Minsky (iv) Herbert Simon20252m

    Module 1: Introduction and Search Techniques

    The Turing Test was proposed by

    (i) John McCarthy
    (ii) Alan Turing
    (iii) Marvin Minsky
    (iv) Herbert Simon

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  2. Q1b. Weak AI is also known as (i) Narrow AI (ii) General AI (iii) Strong AI (iv) Super AI20252m

    Module 1: Introduction and Search Techniques

    Weak AI is also known as

    (i) Narrow AI
    (ii) General AI
    (iii) Strong AI
    (iv) Super AI

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  3. Q1c. Breadth First Search is an example of (i) Informed Search (ii) Uninformed Search (iii) Heuristic Search (iv) Local Search20252m

    Module 1: Introduction and Search Techniques

    Breadth First Search is an example of

    (i) Informed Search
    (ii) Uninformed Search
    (iii) Heuristic Search
    (iv) Local Search

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  4. Q1d. Which algorithm is optimal and complete? (i) Depth First Search (ii) Hill Climbing (iii) A* Search (iv) Simulated Annealing20252m

    Module 1: Introduction and Search Techniques

    Which algorithm is optimal and complete?

    (i) Depth First Search
    (ii) Hill Climbing
    (iii) A* Search
    (iv) Simulated Annealing

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  5. Q1e. Heuristic function h(n) is used in (i) Random Search (ii) Brute Force Search (iii) Uninformed Search (iv) Informed Search20252m

    Module 1: Introduction and Search Techniques

    Heuristic function h(n) is used in

    (i) Random Search
    (ii) Brute Force Search
    (iii) Uninformed Search
    (iv) Informed Search

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  6. Q1f. AO* algorithm is used for solving (i) AND-OR graphs (ii) Game trees (iii) Decision trees (iv) Neural networks20252m

    Module 1: Introduction and Search Techniques

    AO* algorithm is used for solving

    (i) AND-OR graphs
    (ii) Game trees
    (iii) Decision trees
    (iv) Neural networks

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  7. Q1g. Constraint Satisfaction Problems are usually solved using (i) Backtracking (ii) Breadth First Search (iii) A* Search (iv) Alpha-Beta Pruning20252m

    Module 1: Introduction and Search Techniques

    Constraint Satisfaction Problems are usually solved using

    (i) Backtracking
    (ii) Breadth First Search
    (iii) A* Search
    (iv) Alpha-Beta Pruning

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  8. Q1h. Which of the following is a stochastic search method? (i) Breadth First Search (ii) Particle Swarm Optimization (iii) Depth First Search (iv) A* Search20252m

    Module 1: Introduction and Search Techniques

    Which of the following is a stochastic search method?

    (i) Breadth First Search
    (ii) Particle Swarm Optimization
    (iii) Depth First Search
    (iv) A* Search

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  9. Q1i. Bayesian Networks are used to handle (i) Certain knowledge (ii) Uncertain knowledge (iii) Deterministic knowledge (iv) Syntax only20252m

    Module 2: Knowledge Representation and Reasoning

    Bayesian Networks are used to handle

    (i) Certain knowledge
    (ii) Uncertain knowledge
    (iii) Deterministic knowledge
    (iv) Syntax only

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  10. Q1j. Neural Networks are inspired by (i) Genetic evolution (ii) Human brain (iii) Particle movement (iv) Graph theory20252m

    Module 3: Machine Learning Fundamentals

    Neural Networks are inspired by

    (i) Genetic evolution
    (ii) Human brain
    (iii) Particle movement
    (iv) Graph theory

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  11. Q2a. Explain what you understand by Artificial Intelligence. Describe the Turing Test in detail and discuss its significance in the field of AI.20257m

    Module 1: Introduction and Search Techniques

    Explain what you understand by Artificial Intelligence. Describe the Turing Test in detail and discuss its significance in the field of AI.

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  12. Q2b. Explain the concept of Rational Agents. How do they differ from Reflex Agents?20257m

    Module 1: Introduction and Search Techniques

    Explain the concept of Rational Agents. How do they differ from Reflex Agents?

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  13. Q3a. Evaluate the impact of AI on employment and society.20257m

    Module 1: Introduction and Search Techniques

    Evaluate the impact of AI on employment and society.

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  14. Q3b. Explain Breadth First Search and Depth First Search with examples.20257m

    Module 1: Introduction and Search Techniques

    Explain Breadth First Search and Depth First Search with examples.

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  15. Q4a. Describe the role of heuristics in A* algorithm.20257m

    Module 1: Introduction and Search Techniques

    Describe the role of heuristics in A* algorithm.

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  16. Q4b. "A* algorithm is the best search technique." Do you agree? Justify your answer with reasoning.20257m

    Module 1: Introduction and Search Techniques

    "A* algorithm is the best search technique." Do you agree? Justify your answer with reasoning.

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  17. Q5a. Describe Alpha-Beta Pruning. Why is it used in game playing?20257m

    Module 1: Introduction and Search Techniques

    Describe Alpha-Beta Pruning. Why is it used in game playing?

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  18. Q5b. Describe the working of simulated annealing with suitable example.20257m

    Module 1: Introduction and Search Techniques

    Describe the working of simulated annealing with suitable example.

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  19. Q6a. Explain AO* algorithm and how it differs from A* algorithm.20257m

    Module 1: Introduction and Search Techniques

    Explain AO* algorithm and how it differs from A* algorithm.

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  20. Q6b. Discuss the major challenges in developing a practical Robotics system using AI.20257m

    Module 4: Advanced AI Applications

    Discuss the major challenges in developing a practical Robotics system using AI.

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  21. Q7a. Explain Bayesian Networks and their role in handling uncertainty.20257m

    Module 2: Knowledge Representation and Reasoning

    Explain Bayesian Networks and their role in handling uncertainty.

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  22. Q7b. Convert the following statements into First Order Logic: "All men are mortal. Socrates is a man."20257m

    Module 2: Knowledge Representation and Reasoning

    Convert the following statements into First Order Logic: "All men are mortal. Socrates is a man."

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  23. Q8a. Explain the difference between Supervised, Unsupervised, and Semi-Supervised Learning with examples.20257m

    Module 3: Machine Learning Fundamentals

    Explain the difference between Supervised, Unsupervised, and Semi-Supervised Learning with examples.

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  24. Q8b. Describe the architecture of a simple Artificial Neural Network. Explain the role of activation functions.20257m

    Module 3: Machine Learning Fundamentals

    Describe the architecture of a simple Artificial Neural Network. Explain the role of activation functions.

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  25. Q9a. Write a short note on: Natural Language Processing20257m

    Module 4: Advanced AI Applications

    Write a short note on:

    Natural Language Processing

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  26. Q9b. Write a short note on: Expert Systems20257m

    Module 4: Advanced AI Applications

    Write a short note on:

    Expert Systems

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  27. Q9c. Write a short note on: Deep Learning20257m

    Module 3: Machine Learning Fundamentals

    Write a short note on:

    Deep Learning

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  28. Q9d. Write a short note on: Computer Vision20257m

    Module 4: Advanced AI Applications

    Write a short note on:

    Computer Vision

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