Question:
Which of the following algorithms is NOT an example of uninformed search?
Which of the following algorithms is NOT an example of uninformed search?
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Uninformed search uses no heuristic; A* uses \(f(n)=g(n)+h(n)\), so it belongs to informed search.
Updated On: Jul 22, 2026
- Breadth First Search
- Depth First Search
- A* Search
- Depth-limited Search
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The Correct Option is C
Solution and Explanation
Step 1: Understanding the Concept.
Search algorithms in AI are grouped into two families. Uninformed (also called blind) search algorithms explore the state space using only the problem definition itself, the list of possible moves and a way to check if a state is the goal, with no extra guidance about which direction looks more promising. Informed search algorithms, by contrast, use a heuristic function that estimates how close a state is to the goal, and use that estimate to guide the search more efficiently.
Step 2: Key Formula or Approach.
To classify each option, check whether it relies on a heuristic function \(h(n)\) that estimates remaining distance or cost to the goal. If it does, it is informed search. If it explores purely by the order of the search tree or graph structure, it is uninformed search.
Step 3: Detailed Explanation.
Breadth First Search expands nodes level by level, nearest first, using no heuristic at all, this is uninformed search. Depth First Search dives down one branch as far as possible before backtracking, again with no heuristic, this is also uninformed search. Depth-limited Search is simply Depth First Search with a maximum depth cutoff imposed, it still uses no heuristic guidance, so it remains uninformed search. A* Search is different: it computes \(f(n) = g(n) + h(n)\), where \(g(n)\) is the actual cost so far and \(h(n)\) is a heuristic estimate of the cost remaining to the goal. Because it actively uses this heuristic \(h(n)\) to decide which node to expand next, A* Search is classified as informed search, not uninformed search.
Step 4: Final Answer.
The algorithm that is NOT an example of uninformed search is A* Search, option (C). \[ \boxed{\text{A* Search}} \]
Search algorithms in AI are grouped into two families. Uninformed (also called blind) search algorithms explore the state space using only the problem definition itself, the list of possible moves and a way to check if a state is the goal, with no extra guidance about which direction looks more promising. Informed search algorithms, by contrast, use a heuristic function that estimates how close a state is to the goal, and use that estimate to guide the search more efficiently.
Step 2: Key Formula or Approach.
To classify each option, check whether it relies on a heuristic function \(h(n)\) that estimates remaining distance or cost to the goal. If it does, it is informed search. If it explores purely by the order of the search tree or graph structure, it is uninformed search.
Step 3: Detailed Explanation.
Breadth First Search expands nodes level by level, nearest first, using no heuristic at all, this is uninformed search. Depth First Search dives down one branch as far as possible before backtracking, again with no heuristic, this is also uninformed search. Depth-limited Search is simply Depth First Search with a maximum depth cutoff imposed, it still uses no heuristic guidance, so it remains uninformed search. A* Search is different: it computes \(f(n) = g(n) + h(n)\), where \(g(n)\) is the actual cost so far and \(h(n)\) is a heuristic estimate of the cost remaining to the goal. Because it actively uses this heuristic \(h(n)\) to decide which node to expand next, A* Search is classified as informed search, not uninformed search.
Step 4: Final Answer.
The algorithm that is NOT an example of uninformed search is A* Search, option (C). \[ \boxed{\text{A* Search}} \]
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