Informed Search and Exploration Online Exam Quiz
Informed Search and Exploration GK Quiz. Question and Answers related to Informed Search and Exploration. MCQ (Multiple Choice Questions with answers about Informed Search and Exploration
A* is optimal if h(n) is an admissible heuristic-that is, provided that h(n) never underestimates the cost to reach the goal.
Options
A : TRUE
B : FALSE
C : -
D : -
Best-First search can be implemented using the following data structure.
Options
A : Queue
B : Stack
C : Priority Queue
D : Circular Queue
Best-First search is a type of informed search, which uses __ to choose the best next node for expansion.
Options
A : Evaluation function returning lowest evaluation
B : Evaluation function returning highest evaluation
C : Evaluation function returning lowest & highest evaluation
D : None of them is applicable
Greedy search strategy chooses the node for expansion in ___
Options
A : Shallowest
B : Deepest
C : The one closest to the goal node
D : Minimum heuristic cost
Heuristic function h(n) is __
Options
A : Lowest path cost
B : Cheapest path from root to goal node
C : Estimated cost of cheapest path from root to goal node
D : Average path cost
The name ?best-first search? is a venerable but inaccurate one. After all, if we could really expand the best node first, it would not be a search at all; it would be a straight march to the goal. All we can do is choose the node that appears to be best according to the evaluation function.
Options
A : TRUE
B : FALSE
C : -
D : -
The original LISP machines produced by both LMI and Symbolics were based on research performed at __
Options
A : CMU
B : MIT
C : Stanford University
D : RAMD
The search strategy the uses a problem specific knowledge is known as ___
Options
A : Informed Search
B : Best First Search
C : Heuristic Search
D : All of the mentioned
Uninformed search strategies are better than informed search strategies.
Options
A : TRUE
B : FALSE
C : -
D : -
What is the evaluation function in A* approach?
Options
A : Heuristic function
B : Path cost from start node to current node
C : Path cost from start node to current node + Heuristic cost
D : Average of Path cost from start node to current node and Heuristic cost