chapter
    Artificial Intelligence PYQs for GATE DA

    GATE DA Artificial Intelligence: 2 units and 4 chapters, weightage from 14 previous year questions across 3 papers, a study order by exam weight and 0 practic

    A question from this chapter

    Question 1
    2026 PYQ

    Which of the following algorithms is NOT an example of uninformed search?

    Question 2
    2026 PYQ
    Consider the game tree for a two-player turn-taking minimax game as shown in the figure. The value of a terminal node represents the utility of the game state if the game ends there. The numbers written next to the edges denote the strategies.

    There are two players MAX and MIN. At any particular state of the game, MAX prefers to move to a state of maximum value. On the other hand, MIN prefers to move to a state of minimum value.

    Suppose MAX starts the game at the root and has three strategies: 1, 2 and 3. Next, MIN plays and also has three strategies: 1, 2 and 3. The game ends there. Both players always take optimal strategies throughout the game.

    At the root, the best strategy for MAX is ___________ . (Answer in integer)
    MAX MIN 1 2 3 1 2 3 8 6 −1 1 2 3 1 5 7 1 2 3 −4 −3 −12
    Question 3
    2026 PYQ
    Let be a predicate.

    Which of the following statements is/are NOT valid in first-order logic?
    Question 4
    2025 PYQ

    Which of the following statements is/are correct in a Bayesian network?

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    Artificial Intelligence PYQs for GATE DA

    GATE DA Artificial Intelligence: 2 units and 4 chapters, weightage from 14 previous year questions across 3 papers, a study order by exam weight and 0 practice questions.

    About Artificial Intelligence Previous Year Questions (PYQs)

    14 previous year questions from Artificial Intelligence in GATE DA, grouped by chapter with the exam year, answer key and step-by-step solution for each.

    GATE DA Artificial Intelligence Unit-wise Weightage from Past Papers

    We counted every GATE DA Artificial Intelligence previous year question in our bank (14 questions from 3 papers) and grouped them by unit.

    UnitChaptersPYQsShare of sectionAvg per paper
    Search2750%2.3
    Knowledge Representation and Reasoning2750%2.3

    Suggested Artificial Intelligence Study Order for GATE DA

    1. Search: 50% of past Artificial Intelligence questions, about 2.3 per paper.
    2. Knowledge Representation and Reasoning: 50% of past Artificial Intelligence questions, about 2.3 per paper.

    Start where the marks are. Units at the top of this list have appeared most often in past GATE DA papers.

    Units in GATE DA Artificial Intelligence

    All Artificial Intelligence chapters

    One Solved Question from Each Artificial Intelligence Chapter

    Question 1 · Uninformed Search and Heuristic Search · 2026 MCQ

    Which of the following algorithms is NOT an example of uninformed search?

    1. A.

      Breadth First Search

    2. B.

      Depth First Search

    3. C.

      A* Search

    4. D.

      Depth-limited Search

    Question 2 · Adversarial Search, Minimax and Alpha-Beta Pruning · 2026 NAT
    Consider the game tree for a two-player turn-taking minimax game as shown in the figure. The value of a terminal node represents the utility of the game state if the game ends there. The numbers written next to the edges denote the strategies.

    There are two players MAX and MIN. At any particular state of the game, MAX prefers to move to a state of maximum value. On the other hand, MIN prefers to move to a state of minimum value.

    Suppose MAX starts the game at the root and has three strategies: 1, 2 and 3. Next, MIN plays and also has three strategies: 1, 2 and 3. The game ends there. Both players always take optimal strategies throughout the game.

    At the root, the best strategy for MAX is ___________ . (Answer in integer)
    MAX MIN 1 2 3 1 2 3 8 6 −1 1 2 3 1 5 7 1 2 3 −4 −3 −12
    Question 3 · Logic, First-Order Representation and Entailment · 2026 MSQ
    Let be a predicate.

    Which of the following statements is/are NOT valid in first-order logic?
    1. A.

    2. B.

    3. C.

    4. D.

    Question 4 · Bayesian Networks and Probabilistic Inference · 2025 MSQ

    Which of the following statements is/are correct in a Bayesian network?

    1. A.

      Variable elimination is an approximate inference algorithm

    2. B.

      Gibbs sampling is an exact inference algorithm

    3. C.

      Variable elimination is used to determine conditional probabilities

    4. D.

      Rejection sampling is an approximate inference algorithm