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LicenseComputer9. Artificial-intelligence-and-neural-networksMCQsset-3

set-3

134. ______ is similar to Hill climbing searching but with revising or backtracking.

  1. Depth first search
  2. Breadth first search
  3. Best first search
  4. Binary Search
Show me the answer

Answer: 3. Best first search

Explanation:

  • Best-First Search is similar to Hill Climbing but allows for revising or backtracking.
  • It uses a heuristic function to guide the search.

135. The best first search uses the concept of a ______ and heuristic search.

  1. Circular queue
  2. Linear queue
  3. Priority queue
  4. Stack
Show me the answer

Answer: 3. Priority queue

Explanation:

  • Best-First Search uses a priority queue to prioritize nodes based on a heuristic function.
  • This ensures that the most promising nodes are explored first.

136. ______ is the time and ______ is the space complexity of Best first search. Where b= branching factor and d= depth.

  1. O(bd−1)O(b^{d-1}), O(bd−1)O(b^{d-1})
  2. O(bd+1)O(b^{d+1}), O(bd+1)O(b^{d+1})
  3. O(bd−1)O(b^{d-1}), O(bd+1)O(b^{d+1})
  4. O(bd2)O(bd^2), O(bd)O(bd)
Show me the answer

Answer: 1. O(bd−1)O(b^{d-1}), O(bd−1)O(b^{d-1})

Explanation:

  • The time complexity of Best-First Search is O(bd−1)O(b^{d-1}).
  • The space complexity is also O(bd−1)O(b^{d-1}) because it stores nodes in the priority queue.

137. Greedy best first search evaluates nodes by using only ______

  1. Linear function
  2. Non-linear function
  3. Friend function
  4. Heuristic function
Show me the answer

Answer: 4. Heuristic function

Explanation:

  • Greedy Best-First Search evaluates nodes using only a heuristic function.
  • This function estimates the cost to reach the goal from the current node.

138. Why greedy best first search is not complete?

  1. Because it can override the heuristic function
  2. Because it can traverse to outer loop
  3. Because it can get stuck in loop
  4. None of the above
Show me the answer

Answer: 3. Because it can get stuck in loop

Explanation:

  • Greedy Best-First Search is not complete because it can get stuck in loops.
  • It does not guarantee finding a solution if one exists.

139. ______ is the time and ______ is the space complexity of Greedy Best first search.

  1. O(bm)O(bm), O(bm)O(b^{m})
  2. O(bm)O(b^{m}), O(bm)O(bm)
  3. O(bm+1)O(b^{m+1}), O(bm+1)O(b^{m+1})
  4. O(bm)O(b^{m}), O(bm)O(b^{m})
Show me the answer

Answer: 4. O(bm)O(b^{m}), O(bm)O(b^{m})

Explanation:

  • The time complexity of Greedy Best-First Search is O(bm)O(b^{m}).
  • The space complexity is also O(bm)O(b^{m}) because it stores nodes in the priority queue.

140. The main idea of A* searching is to a ______

  1. Do not expand expensive path
  2. Expand expensive path
  3. All path cost are same in searching
  4. None of above
Show me the answer

Answer: 1. Do not expand expensive path

Explanation:

  • The main idea of A Search* is to avoid expanding expensive paths by using a heuristic function.
  • It combines the cost to reach the current node and the estimated cost to reach the goal.

141. Evaluation function is ______ for A* searching, where, g(n) - cost so far to reach n h(n) - estimated cost to goal from n f(n) - estimated total cost of path through n to goal.

  1. f(n)=g(n)/h(n)f(n) = g(n) / h(n)
  2. f(n)=g(n)−h(n)f(n) = g(n) - h(n)
  3. f(n)=g(n)+h(n)f(n) = g(n) + h(n)
  4. f(n)=g(n)×h(n)f(n) = g(n) \times h(n)
Show me the answer

Answer: 3. f(n)=g(n)+h(n)f(n) = g(n) + h(n)

Explanation:

  • The evaluation function in A* Search is f(n)=g(n)+h(n)f(n) = g(n) + h(n).
  • Here, g(n)g(n) is the cost to reach node nn, and h(n)h(n) is the estimated cost to reach the goal from nn.

142. A* search uses an ______ heuristic; that is, h(n) < h*(n) where h*(n) is the true cost from ‘n’.

  1. Non- admissible
  2. Admissible
  3. Anchoring
  4. Constant
Show me the answer

Answer: 2. Admissible

Explanation:

  • A Search* uses an admissible heuristic, meaning h(n)<h∗(n)h(n) < h^*(n).
  • This ensures that the heuristic never overestimates the true cost to reach the goal.

143. When should A* searching terminate?

  1. After we enqueue a goal
  2. After we dequeue a goal
  3. No enqueue and dequeue
  4. None of above
Show me the answer

Answer: 2. After we dequeue a goal

Explanation:

  • A Search* terminates when a goal node is dequeued from the priority queue.
  • This ensures that the optimal path has been found.

144. A* search theorem states that:

  1. If h(n) is not admissible, A* using TREE-SEARCH is optimal.
  2. If h(n) is admissible, A* using TREE-SEARCH is optimal.
  3. If h(n) is admissible, A* using TREE-SEARCH is not optimal.
  4. If h(n) is not admissible, A* using TREE-SEARCH is also not optimal.
Show me the answer

Answer: 2. If h(n) is admissible, A* using TREE-SEARCH is optimal.

Explanation:

  • The A Search Theorem* states that if the heuristic h(n)h(n) is admissible, A* using TREE-SEARCH is optimal.
  • This means it will find the least-cost path to the goal.

145. ______ is the time and ______ is the space complexity of A* Search. Where b= branching factor and d= depth

  1. O(bd+1)O(b^{d+1}), O(bb)O(b^b)
  2. O(bb)O(b^b), O(bb)O(b^b)
  3. O(bd+1)O(b^{d+1}), O(bd+1)O(b^{d+1})
  4. O(bb)O(b^b), O(bd+1)O(b^{d+1})
Show me the answer

Answer: 2. O(bb)O(b^b), O(bb)O(b^b)

Explanation:

  • The time complexity of A* Search is O(bb)O(b^b).
  • The space complexity is also O(bb)O(b^b) because it stores nodes in the priority queue.

146. A* is an admissible algorithm that ______ optimal solution.

  1. Does not guarantee
  2. Guarantee
  3. Partially guarantee
  4. None of above
Show me the answer

Answer: 2. Guarantee

Explanation:

  • A Search* is an admissible algorithm that guarantees an optimal solution.
  • It finds the least-cost path to the goal if the heuristic is admissible.

147. The main application of A* Search Algorithm is: Path/ Routing problems can be solved by using A* Searching algorithm.

  1. True
  2. False
  3. Partially True
  4. None of above
Show me the answer

Answer: 1. True

Explanation:

  • A Search* is widely used for solving pathfinding and routing problems.
  • It is efficient and guarantees the optimal path if the heuristic is admissible.

148. A* using Tree search is optimal if heuristic is ______.

  1. Constant
  2. Admissible
  3. Anchoring
  4. Representative
Show me the answer

Answer: 2. Admissible

Explanation:

  • A Search* using Tree Search is optimal if the heuristic is admissible.
  • This means the heuristic never overestimates the true cost to reach the goal.

149. A* using Graph search is optimal if heuristic is ______.

  1. Constant
  2. Admissible
  3. Representative
  4. Anchoring
Show me the answer

Answer: 2. Admissible

Explanation:

  • A Search* using Graph Search is optimal if the heuristic is admissible.
  • This ensures that the algorithm finds the least-cost path to the goal.

150. ______ is sometimes called greedy local search because it grabs a good neighbor state without thinking ahead about where to go next.

  1. Mini Max
  2. Alpha beta pruning
  3. Hill Climbing
  4. BFS
Show me the answer

Answer: 3. Hill Climbing

Explanation:

  • Hill Climbing is sometimes called greedy local search because it selects the best neighbor state without considering future steps.
  • It focuses on immediate improvements rather than long-term planning.
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