Artificial intelligence and robotics mcqs unit 1

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Artificial intelligence and robotics mcqs unit 1

Artificial intelligence and robotics mcq questions and answers

1. Depth First Search is equivalent to which of the traversal in the Binary Trees?

  1. Pre-order Traversal
  2. Post-order Traversal
  3. Level-order Traversal
  4. In-order Traversal
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Pre-order Traversal

2. Time Complexity of DFS is? (V – number of vertices, E – number of edges)

  1. O(E)
  2. O(V)
  3. O(V+E)
  4. O(V*E)
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O(V+E)

3. The Depth First Search traversal of a graph will result into?

  1. Linked List
  2. Tree
  3. Graph with back edges
  4. Array
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Tree

4. Which algorithm is used in graph traversal and path finding?

  1. C*
  2. A*
  3. E*
  4. D*
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A*

5. Branch and bound is a __

  1. data structure
  2. type of tree
  3. sorting algorithm
  4. problem solving technique
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problem solving technique

6. Which data structure is used for implementing a LIFO branch and bound strategy?

  1. stack
  2. queue
  3. array
  4. linked list

stack

7. Which data structure is used for implementing a FIFO branch and bound strategy

  1. stack
  2. queue
  3. array
  4. linked list
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queue

8. Which of the following can traverse the state space tree only in DFS manner?

  1. branch and bound
  2. dynamic programming
  3. greedy algorithm
  4. backtracking
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backtracking

9. Which of the following is false in the case of a spanning tree of a graph G?

  1. It is tree that spans G
  2. It is a subgraph of the G
  3. It can be either cyclic or acyclic
  4. It includes every vertex of the G

It can be either cyclic or acyclic

10. Consider a undirected graph G with vertices { A, B, C, D, E}. In graph G, every edge has distinct weight. Edge CD is edge with minimum weight and edge AB is edge with maximum weight. Then, which of the following is false?

  1. Every minimum spanning tree of G must contain CD
  2. If AB is in a minimum spanning tree, then its removal must disconnect G
  3. No minimum spanning tree contains AB
  4. G has a unique minimum spanning tree
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No minimum spanning tree contains AB

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11. Which search strategy is also called as blind search?

  1. Uninformed search
  2. Informed search
  3. Simple reflex search
  4. All of the mentioned
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Uninformed search

12. Which search is implemented with an empty first-in-first-out queue?

  1. Depth-first search
  2. Breadth-first search
  3. Bidirectional search
  4. None of the mentioned

Breadth-first search

13. How many successors are generated in backtracking search?

  1. 1
  2. 2
  3. 3
  4. 4
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1

14. Which algorithm is used to solve any kind of problem?

  1. Breadth-first algorithm
  2. Tree algorithm
  3. Bidirectional search algorithm
  4. None of the mentioned

Tree algorithm

15. Which search algorithm imposes a fixed depth limit on nodes?

  1. Depth-limited search
  2. Depth-first search
  3. Iterative deepening search
  4. Bidirectional search

Depth-limited search

16. Which search implements stack operation for searching the states?

  1. Depth-limited search
  2. Depth-first search
  3. Iterative deepening search
  4. Bidirectional search
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Depth-first search

17.Strategies that know whether one non-goal state is “more promising” than another are called _

  1. Informed & Unformed Search
  2. Unformed Search
  3. Heuristic & Unformed Search
  4. Informed & Heuristic Search

Informed & Heuristic Search

18. What is the other name of informed search strategy?

  1. Simple search
  2. Heuristic search
  3. Online search
  4. None of the mentioned

Heuristic search

19. uniform-cost search expands the node n with the __

  1. Lowest path cost
  2. Heuristic cost
  3. Highest path cost
  4. Average path cost
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Lowest path cost

artificial intelligence and robotics mcqs questions

20. Which search uses the problem specific knowledge beyond the definition of the problem?

  1. Informed search
  2. Depth-first search
  3. Breadth-first search
  4. Uninformed search

Informed search

21. A heuristic is a way of trying _

  1. To discover something or an idea embedded in a program
  2. To search and measure how far a node in a search tree seems to be from a goal
  3. To compare two nodes in a search tree to see if one is better than another
  4. All of the mentioned

All of the mentioned

22. A* algorithm is based on _

  1. Breadth-First-Search
  2. Depth-First –Search
  3. Best-First-Search
  4. Hill climbing
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Best-First-Search

23. Best-First search is a type of informed search, which uses ____ to choose the best next node for expansion

  1. Evaluation function returning lowest evaluation
  2. Evaluation function returning highest evaluation
  3. Evaluation function returning lowest & highest evaluation
  4. None of them is applicable

Evaluation function returning lowest evaluation

24. Heuristic function h(n) is __

  1. Lowest path cost
  2. Cheapest path from root to goal node
  3. Estimated cost of cheapest path from root to goal node
  4. Average path cost
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Estimated cost of cheapest path from root to goal node

25. Greedy search strategy chooses the node for expansion in _

  1. Shallowest
  2. Deepest
  3. The one closest to the goal node
  4. Minimum heuristic cost

The one closest to the goal node

26. What is the evaluation function in greedy approach?

  1. Heuristic function
  2. Path cost from start node to current node
  3. Path cost from start node to current node + Heuristic cost
  4. Average of Path cost from start node to current node and Heuristic cost

Heuristic function

27. What is the evaluation function in A* approach?

  1. Heuristic function
  2. Path cost from start node to current node
  3. Path cost from start node to current node + Heuristic cost
  4. Average of Path cost from start node to current node and Heuristic cost

Path cost from start node to current node + Heuristic cost

28. In many problems the path to goal is irrelevant, this class of problems can be solved using __

  1. Informed Search Techniques
  2. Uninformed Search Techniques
  3. Local Search Techniques
  4. Informed & Uninformed Search Techniques
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Local Search Techniques

29. Though local search algorithms are not systematic, key advantages would include __

  1. Less memory
  2. More time
  3. Finds a solution in large infinite space
  4. Less memory & Finds a solution in large infinite space

Less memory & Finds a solution in large infinite space

30. ___ Is an algorithm, a loop that continually moves in the direction of increasing value – that is uphill.

  1. Up-Hill Search
  2. Hill-Climbing
  3. Hill algorithm
  4. Reverse-Down-Hill search

Hill-Climbing

31. When will Hill-Climbing algorithm terminate?

  1. Stopping criterion met
  2. Global Min/Max is achieved
  3. No neighbor has higher value
  4. All of the mentioned

No neighbor has higher value

32. Hill climbing sometimes called __ because it grabs a good neighbor state without thinking ahead about where to go next

  1. Needy local search
  2. Heuristic local search
  3. Greedy local search
  4. Optimal local search
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Greedy local search

33. Searching using query on Internet is, use of _ type of agent

  1. Offline agent
  2. Online agent
  3. Both Offline & Online agent
  4. Goal Based & Online agent

Goal Based & Online agent

34. Best-First search can be implemented using the following data structure

  1. Queue
  2. Stack
  3. Priority Queue
  4. Circular Queue
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Priority Queue

35. Which is used to improve the performance of heuristic search?

  1. Quality of nodes
  2. Quality of heuristic function
  3. Simple form of nodes
  4. None of the mentioned

Quality of heuristic function

36. Which search is complete and optimal when h(n) is consistent?

  1. Best-first search
  2. Depth-first search
  3. Both Best-first & Depth-first search
  4. A* search

A* search

37. Which method is used to search better by learning?

  1. Best-first search
  2. Depth-first search
  3. Metalevel state space
  4. None of the mentioned

TMetalevel state space

38. Which search uses only the linear space for searching?

  1. Best-first search
  2. Recursive best-first search
  3. Depth-first search
  4. None of the mentioned
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Recursive best-first search

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

  1. f(n) != h(n)
  2. f(n) < h(n)
  3. f(n) = h(n)
  4. f(n) > h(n)

f(n) = h(n)

40. Which function will select the lowest expansion node at first for evaluation?

  1. Greedy best-first search
  2. Best-first search
  3. Depth-first search
  4. None of the mentioned
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Best-first search

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