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Welcome to the Expert Systems MCQs Page

Dive deep into the fascinating world of Expert Systems with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Expert Systems, a crucial aspect of Artificial Intelligence. In this section, you will encounter a diverse range of MCQs that cover various aspects of Expert Systems, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Artificial Intelligence.

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Check out the MCQs below to embark on an enriching journey through Expert Systems. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Artificial Intelligence.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Expert Systems. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Expert Systems MCQs | Page 3 of 4

Explore more Topics under Artificial Intelligence

Q21.
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

Discuss
Answer: (d).all of the above
Q22.
Which of the following are Informed search algorithms?

a.

best first search

b.

a* search

c.

iterative deeping search

d.

both a and b

Discuss
Answer: (d).both a and b
Q23.
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

Discuss
Answer: (b).guaranteed
Q24.
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

Discuss
Answer: (c).iterative deepening depth first search
Q25.
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)

Discuss
Answer: (d).h(n)<= h*(n)
Q26.
The efficiency of A* algorithm depends on __________________________.

a.

depth

b.

the quality of heuristic

c.

unknown nodes

d.

none of the above

Discuss
Answer: (b).the quality of heuristic
Q27.
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.

Discuss
Answer: (a).when no successor of the node has better heuristic value.
Q28.
What is true about variable neighborhood function?

a.

neighbourhood functions that are sparse lead to quicker movement during search

b.

algorithm has to inspect very fewer neighbours

c.

vdn stars searching with sparse neighbourhood functions, when it reaches an optimum, it switches to denser function.

d.

all of the above

Discuss
Answer: (d).all of the above
Q29.
_______________________requires Linear Space but uses backtracking.

a.

breadth first search

b.

recursive best first search (rbfs)

c.

a*

d.

ida*

Discuss
Answer: (b).recursive best first search (rbfs)
Q30.
Which property asks that the algorithm is locally admissible?

a.

admissibility

b.

monotonicity

c.

informedness

d.

none of the above

Discuss
Answer: (b).monotonicity
Page 3 of 4

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