ARTIFICIAL INTELLIGENCE 2019 MCA 4th Sem AKTU

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Paper Id: 214239 Roll No. _____________________

MCA

(SEM IV) THEORY EXAMINATION 2018-19

ARTIFICIAL INTELLIGENCE

Time: 3 Hours Total Marks: 70

Note: Attempt all Sections. If require any missing data; then choose suitably.

SECTION A

1. Attempt all questions in brief. 2 x 7 = 14

    (a) Name the elements of an agent.

    (b) Summarize the factors that make up rationality.

    (c) What do you infer from hill-climbing search algorithm?

    (d) Compare propositional logic and predicate logic.

    (e) Justify the usage of universal and existential quantifier with an example.

    (f) Give the heuristic function for shortest path problem.

    (g) Which algorithm is more similar to backward chaining algorithm? Write its algorithm.

SECTION B

2. Attempt any three of the following: 7 x 3 = 21

    (a) You have three jugs measuring 12 gallons, 8 gallons and 3 gallons and a water faucet. You need to measure out exactly one gallon.

    (b) Describe the planning method based on hierarchical task networks with an example.

    (c) Discuss the different design issues to be solved to use hidden markov model for real world application.

    (d) Assume two player min and max, play nim (as described above). Min plays first’ If a terminal state if the search tree developed above is a win for min, a utility function zero is designed to that state. A utility function I is assigned to a state, if max wins the game. Apply the minimax algorithm to the search tree to assign utility function to all states in the search tree.

    (e) Give the completeness proof of resolution.

SECTION C

3. Attempt any one part of the following: 7 x 1 = 7

    a. Implement Search Algorithm described in this lecture in LISP and/or C. Commem on how suited each language would be for each type of search?

    b. How suited would PROLOG be in implementing the search algorithms? Comment on how this might be done and what difficulties might exist.

4. Attempt any one part of the following: 7 x 1 = 7

    a. Trace the constraint satisfaction procedure to solve the following crypt arithmetic problem:

       CROSS

       +ROADS

         ———-

     DANGER

    b. Discuss how constraint satisfaction might work it implemented its search strategy via:

      i. depth first search

     ii. breadth first search

    iii. best first search

5. Attempt any one part of the following: 7 x 1 = 7

    a. Represent the following in partitioned semantic networks:

       i. Every player kicked a fall.

      ii. All players like the referee

     iii. Andrew believes that there is a fish with lungs.

    b. Pick a problem area and represent the knowledge in frame based system.

6. Attempt any one part of the following: 7 x 1 = 7

    a. Describe a rational agent function for the modified performance measure that deducts one point for each movement. Does the corresponding agent program require internal.

    b. Discuss possible agent designs for the cases in which clean square can become dirty and the geography of the environment is unknown. Does it make sense for the agent to learn from its experience in the cases? If so, what should it learn?

7. Attempt any one part of the following: 7 x 1 = 7

    (a) Discuss back propagation algorithm for learning in multi-layer neural network.

    (b) Explain the concept of forward and backward state space search in detail.

Thank You!