Artificial Intelligence PYQ 2024-25 AKTU Question Paper

AKTU · BTECH · Semester 5 · Artificial Intelligence · Session 2024-25 · PYQ

AKTU Artificial Intelligence previous year question paper 2024-25 for B.Tech Semester 5. Covers Introduction, Problem Solving Methods, Knowledge…

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Artificial Intelligence AKTU syllabus

  1. Unit 1: Introduction
  2. Unit 2: Problem Solving Methods
  3. Unit 3: Knowledge Representation
  4. Unit 4: Software Agents
  5. Unit 5: Applications

Questions in Artificial Intelligence AKTU PYQ 2024-25

  1. Q1a. Define Artificial Intelligence. (2 marks, 2024-25)
  2. Q1b. Define "problem-solving" in AI. (2 marks, 2024-25)
  3. Q1c. Define problem-solving in the context of AI. (2 marks, 2024-25)
  4. Q1d. What is a Constraint Satisfaction Problem (CSP)? (2 marks, 2024-25)
  5. Q1e. What is First Order Predicate Logic (FOPL)? (2 marks, 2024-25)
  6. Q1f. Define an intelligent agent. (2 marks, 2024-25)
  7. Q1g. Explain the concept of machine translation. (2 marks, 2024-25)
  8. Q2a. Compare and contrast different types of Intelligent Agents (Simple Reflex, Model-Based, Goal-Based, and Utility-Based). (7 marks, 2024-25)
  9. Q2b. Explain the difference between uninformed and informed search strategies with examples. (7 marks, 2024-25)
  10. Q2c. Discuss different types of knowledge representation techniques in AI. (7 marks, 2024-25)
  11. Q2d. Describe the negotiation process in multi-agent systems with examples. (7 marks, 2024-25)
  12. Q2e. Discuss the process and significance of information retrieval in AI. (7 marks, 2024-25)
  13. Q3a. Explain the evolution of Artificial Intelligence from symbolic AI to modern machine learning. (7 marks, 2024-25)
  14. Q3b. Explain the role of AI in enhancing decision-making processes in business applications. (7 marks, 2024-25)
  15. Q4a. Discuss the structure and components of a Constraint Satisfaction Problem (CSP). (7 marks, 2024-25)
  16. Q4b. Describe the process of solving a Sudoku puzzle using CSP methods. (7 marks, 2024-25)
  17. Q5a. Compare semantic networks and frames as knowledge representation methods. (7 marks, 2024-25)
  18. Q5b. Explain how reasoning systems are designed for decision-making in AI. (7 marks, 2024-25)
  19. Q6a. Explain how argumentation is used for resolving conflicts in multi-agent systems. (7 marks, 2024-25)
  20. Q6b. Explain how autonomous agents manage decision-making and execution. (7 marks, 2024-25)
  21. Q7a. Explain the steps involved in extracting structured information from unstructured data. (7 marks, 2024-25)
  22. Q7b. Explain how tokenization impacts natural language processing tasks. (7 marks, 2024-25)

AKTU paper codes: BCAI501, KCAI501

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