Artificial Intelligence and Robotics (AIR) MCQs | Page - 7

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Madhu • 12.07K Points
Tutor II 

Q. The start node for search in plan space planning is______

(A) bfs
(B) dfs
(C) both dfs and bfs
(D) a*
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M

Madhu • 12.07K Points
Tutor II 

Q. In which chaining, the Left-Hand side is used to match the rules and Right-Hand side is used to check the effect of using the rule.

(A) forward chaining
(B) backward chaining
(C) reverse chaining
(D) both b & c
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M

Madhu • 12.07K Points
Tutor II 

Q. The components of Expert system are?

(A) a set of rules, the inference engine (ie), forward chaining
(B) a set of rules, backward chaining, a working memory (wm)
(C) a set of rules, the inference engine (ie), a working memory (wm)
(D) a set of rules, forward chaining, backward chaining
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M

Madhu • 12.07K Points
Tutor II 

Q. What is true about Artificial Intelligence?

(A) the ability to solve problems”.
(B) the ability to act rationally.
(C) the ability to act like humans
(D) all of the above
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M

Madhu • 12.07K Points
Tutor II 

Q. Which of the following are Informed search algorithms?

(A) best first search
(B) a* search
(C) iterative deeping search
(D) both a & b
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M

Madhu • 12.07K Points
Tutor II 

Q. If there is a solution, breadth first search is _______________to find it

(A) difficult
(B) guaranteed
(C) not able to find
(D) none of the above
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M

Madhu • 12.07K Points
Tutor II 

Q. Which search strategy is combining the benefits of both BFS and DFS?

(A) depth limited search
(B) a*
(C) iterative deepening depth first search
(D) best first search
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M

Madhu • 12.07K Points
Tutor II 

Q. Admissibility of the heuristic function is given as:

(A) h(n)>= h*(n)
(B) h(n)< h*(n)
(C) h(n)== h*(n)
(D) h(n)<= h*(n)
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M

Madhu • 12.07K Points
Tutor II 

Q. The efficiency of A* algorithm depends on ___________________

(A) depth
(B) the quality of heuristic
(C) unknown nodes
(D) none of the above
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M

Madhu • 12.07K Points
Tutor II 

Q. What is the termination criteria in Hill climbing?

(A) when no successor of the node has better heuristic value.
(B) when successor of the node has better heuristic value.
(C) when no ancestor of the node has better heuristic value.
(D) when ancestor of the node has better heuristic value.
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