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BSC CSIT Semester 4 Artificial Intelligence () Questions & Answers | Past TU Exam Papers

Practice from Artificial Intelligence with detailed solutions and model answers from past Tribhuvan University exams.

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How is informed search different from uninformed search? Create a state space with appropriate heuristics, now illustrate how hill climbing search expands nodes to reach a goal. Modify the state space heuristics and demonstrate when the hill climbing will not be complete.

HardTHEORY10 marks2081(TU Final)

How uniform cost search is used to search goal in the state apace ? Illustrate with example.

MediumTHEORY5 marks2081(TU Final)

How is minmax algorithm used in game search? Consider state space is defined by a collection of pairs like (A, B) representing paths between states A and B. Construct state space for following and use a minmax algorithm

(A, B), (A, C), (B, D), (D, E), (C, F), (C, G), (D, H), (D, I), (E, J), (F, K), (F, L), (G, M), (G, N).

The utilities for states H, I, J, K, L, M, N are 1, 3, 2, 6, 3, 4, 1 respectively.

MediumTHEORY5 marks2081(TU Final)

Define state space graph. Differenciate between A* search and greedy best first search.

HardTHEORY10 marks2080(TU Final)

What is game search? How minmax search used in game playing ? Illustrate with an example.

MediumTHEORY5 marks2080(TU Final)

What is constraint satisfaction problem? Illustrate graph coloring problem as constraint satisfaction problem.

MediumTHEORY5 marks2080(TU Final)

Define admissible heuristic with an example. Explain the working mechanism and limitations of hill climbing search.

HardTHEORY10 marks2079(TU Final)

How do you define problem? What are criteria for defining problem? Compare Constraint Satisfaction Problem and Real World Problem in detail with appropriate example.

HardTHEORY10 marks2079(TU Final)

What is state space representation? Illustrate with one example.

HardTHEORY5 marks2079(TU Final)

Define game. Write the benefits and limitations of depth limited search.

HardTHEORY5 marks2079(TU Final)

How informed search are different than uniformed? Given following stae space, illustrate how depth limited search and iterative depending dearch works? Use your own assumption for depth search.

image

Hence, A is start and K is goal.

HardTHEORY10 marks2078(TU Final)

Consider following facts

Every traffic chases driver. Every driver who horns is smart. No traffic catches any smart driver. Any traffic who chases some driver but does not catch him frusted. Now configure FoPL knowledge base for above statements. Use resolution algorithm to draw a conclusion that “If all drivers horn, then all traffics are frusted.”

HardTHEORY10 marks2078(TU Final)

Given following search space, determine if these exists any alpha and beta cutoffs.

image

MediumTHEORY5 marks2078(TU Final)

Construct a state space with appropriate heuristics and local costs. Show that Greedy Best First search is not complete for the state space. Also illustrate A* is complete and guarantees solution for the same state space.

HardTHEORY10 marks2076(TU Final)

Illustrate with an example, how uniform cost search algorithm can be used for finding goal in a state space.

MediumTHEORY5 marks2076(TU Final)

Define state space graph. Differentiate between A* search and greedy best first search.

HardTHEORY10 marks2080(TU Final)

What is game search? How Min–Max search is used in game playing? Illustrate with an example.

MediumTHEORY5 marks2080(TU Final)

What is constraint satisfaction problem? Illustrate graph coloring problem as constraint satisfaction problem.

MediumTHEORY5 marks2080(TU Final)
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Unit III: Problem Solving by Searching (9 Hrs.) chapter questions with answers for Artificial Intelligence (BSC CSIT Semester 4). Prepare for TU exams with our comprehensive question bank and model answers.