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# AI Problem Solving Agents MCQ

Problem Solving Agents MCQs : This section focuses on "Problem Solving Agents" in Artificial Intelligence. These Multiple Choice Questions (mcq) should be practiced to improve the AI skills required for various interviews (campus interviews, walk-in interviews, company interviews), placements, entrance exams and other competitive examinations.

1. What is the main task of a problem-solving agent?

A. Solve the given problem and reach to goal
B. To find out which sequence of action will get it to the goal state
C. Both A and B
D. None of the Above

2. What is Branching Factor?

A. Length of the shortest path from initial state to goal state.
B. The average number of child nodes in the problem space graph.
C. A property of an algorithm to always find an optimal solution.
D. None of the Above

3. What is Initial state + Goal state in Search Terminology?

A. Problem Space
B. Problem Instance
C. Problem Space Graph

4. What is Space Complexity of Depth First search algorithm?

A. b
B. b^2
C. b^b
D. b^m

5. What is Time Complexity of Breadth First search algorithm?

A. b
B. b^d
C. b^2
D. b^b

6. The process of removing detail from a given state representation is called ______

A. Extraction
B. Abstraction
C. Information Retrieval
D. Mining of data

7. Depth-First Search is implemented in recursion with _______ data structure.

A. LIFO
B. LILO
C. FIFO
D. FILO

8. Which of the following search algorithm searches forward from initial state and backward from goal state till both meet to identify a common state?

A. Uniform Cost Search
B. Iterative Deepening Depth-First Search
C. Bidirectional Search
D. None of the Above

9. How many types are available in uninformed search method?

A. 2
B. 3
C. 4
D. 5

10. When is breadth-first search is optimal?

A. When there is less number of nodes
B. When all step costs are equal
C. When all step costs are unequal
D. All of the above

11. Which data structure conveniently used to implement BFS?

A. Stacks
B. Queues
C. Priority Queues
D. None of the Above

12. uniform-cost search expands the node n with the __________

A. Lowest path cost
B. Heuristic cost
C. Highest path cost
D. Average path cost

13. How many types of informed search method are in artificial intelligence?

A. 2
B. 3
C. 4
D. 5

14. What is the heuristic function of greedy best-first search?

A. f(n) != h(n)
B. f(n) < h(n)
C. f(n) = h(n)
D. f(n) > h(n)

15. Greedy search strategy chooses the node for expansion in ___________

A. Shallowest
B. Deepest
C. The one closest to the goal node
D. Minimum heuristic cost

16. A* algorithm is based on __________

B. Depth-First-Search
C. Uniform Cost Search
D. Best-First-Search

17. What is disadvantage of Greedy Best First Search?

A. This algorithm is neither complete, nor optimal.
B. It can get stuck in loops. It is not optimal.
C. There can be multiple long paths with the cost ≤ C*
D. may not terminate and go on infinitely on one path

18. When will Hill-Climbing algorithm terminate?

A. Stopping criterion met
B. Global Min/Max is achieved
C. No neighbor has higher value
D. All of the above

19. Searching using query on Internet is, use of ___________ type of agent.

A. Offline agent
B. Online Agent
C. Goal Based
D. Both B and C

20. Is optimality and completeness exist in bidirectional search algorithm?

A. Yes, Yes
B. No, Yes
C. Yes, No
D. No, No