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
View Answer
Ans : C
Explanation: The problem-solving agents are one of the goal-based agents.
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
View Answer
Ans : B
Explanation: Branching Factor : The average number of child nodes in the problem space graph.
3. What is Initial state + Goal state in Search Terminology?
A. Problem Space
B. Problem Instance
C. Problem Space Graph
D. Admissibility
View Answer
Ans : B
Explanation: Problem Instance : It is Initial state + Goal state.
4. What is Space Complexity of Depth First search algorithm?
A. b
B. b^2
C. b^b
D. b^m
View Answer
Ans : D
Explanation: Space Complexity of Depth First search algorithm is b^m
5. What is Time Complexity of Breadth First search algorithm?
A. b
B. b^d
C. b^2
D. b^b
View Answer
Ans : B
Explanation: Time Complexity of Breadth First search algorithm is b^d.
6. The process of removing detail from a given state representation is called ______
A. Extraction
B. Abstraction
C. Information Retrieval
D. Mining of data
View Answer
Ans : B
Explanation: The process of removing detail from a representation is called abstraction.
7. Depth-First Search is implemented in recursion with _______ data structure.
A. LIFO
B. LILO
C. FIFO
D. FILO
View Answer
Ans : A
Explanation: Depth-First Search implemented in recursion with LIFO stack data structure.
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
View Answer
Ans : C
Explanation: Bidirectional Search searches forward from initial state and backward from goal state till both meet to identify a common state.
9. How many types are available in uninformed search method?
A. 2
B. 3
C. 4
D. 5
View Answer
Ans : D
Explanation: The five types of uninformed search method are Breadth-first, Uniform-cost, Depth-first, Depth-limited and Bidirectional search.
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
View Answer
Ans : B
Explanation: Because it always expands the shallowest unexpanded node.
11. Which data structure conveniently used to implement BFS?
A. Stacks
B. Queues
C. Priority Queues
D. None of the Above
View Answer
Ans : B
Explanation: Queue is the most convenient data structure, but memory used to store nodes can be reduced by using circular queues.
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
View Answer
Ans : A
Explanation: Uniform-cost search expands the node n with the lowest path cost. Note that if all step costs are equal, this is identical to breadth-first search.
13. How many types of informed search method are in artificial intelligence?
A. 2
B. 3
C. 4
D. 5
View Answer
Ans : C
Explanation: The four types of informed search method are best-first search, Greedy best-first search, A* search and memory bounded heuristic search.
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)
View Answer
Ans : C
Explanation: f(n) = h(n) is the heuristic function of greedy best-first searc
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
View Answer
Ans : C
Explanation: Sometimes minimum heuristics can be used, sometimes maximum heuristics function can be used. It depends upon the application on which the algorithm is applied.
16. A* algorithm is based on __________
A. Breadth-First-Search
B. Depth-First-Search
C. Uniform Cost Search
D. Best-First-Search
View Answer
Ans : D
Explanation: Best-first-search is giving the idea of optimization and quick choose of path, and all these characteristic lies in A* algorithm.
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
View Answer
Ans : B
Explanation: The disadvantage of Greedy Best First Search is that it can get stuck in loops. It is not optimal.
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
View Answer
Ans : C
Explanation: When no neighbor is having higher value, algorithm terminates fetching local min/max.
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
View Answer
Ans : D
Explanation: Refer to the definitions of both the type of agent.
20. Is optimality and completeness exist in bidirectional search algorithm?
A. Yes, Yes
B. No, Yes
C. Yes, No
D. No, No
View Answer
Ans : A
Explanation: Yes, optimality and completeness both exist in bidirectional search algorithm.
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