Consider f(N) = g(N) + h(N) Where function g is a measure of the cost of…
2014
Consider f(N) = g(N) + h(N) Where function g is a measure of the cost of getting from the start node to the current node N and h is an estimate of additional cost of getting from the current node N to the goal node. Then f(N) = h(N) is used in which one of the following algorithms ?
- A.
A* algorithm
- B.
AO* algorithm
- C.
Greedy best first search algorithm
- D.
Iterative A* algorithm
Attempted by 81 students.
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Correct answer: C
Answer: Greedy best-first search algorithm
Why: Greedy best-first search selects the next node to expand based solely on the heuristic estimate h(N). Setting f(N) = h(N) means the search ranks nodes only by their estimated distance to the goal and ignores the accumulated cost g(N).
Selection criterion: choose the node with the smallest h(N).
Relation to A*: A* uses f(N) = g(N) + h(N), combining the path cost so far with the heuristic. That combination is what gives A* its optimality guarantees when h is admissible.
Optimality: Greedy best-first is not guaranteed to find the least-cost path because it ignores g(N); it can be fast when the heuristic is very informative but may return suboptimal solutions.
Other algorithms: AO* and iterative variants of A* still rely on combining cost estimates and/or using f = g + h (for example, IDA* iteratively increases an f threshold). They do not simply set f(N) = h(N).
Takeaway: If a search uses f(N) = h(N), it is following a greedy best-first strategy—fast but not guaranteed optimal unless additional conditions hold.