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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 4 of 4

Explore more Topics under Artificial Intelligence

Q31.
A* Search Algorithm _______________.

a.

does not expand the node which have the lowest value of f(n),

b.

finds the shortest path through the search space using the heuristic function i.e f(n)=g(n) + h(n)

c.

terminates when the goal node is not found.

d.

all of the above

Discuss
Answer: (b).finds the shortest path through the search space using the heuristic function i.e f(n)=g(n) + h(n)
Q32.
Which is not problem in Hill climing?

a.

plateau

b.

ridges

c.

local maximum

d.

landscape

Discuss
Answer: (d).landscape
Q33.
Tabu search is designed __________________________.

a.

as it does not follow aspiration criteria

b.

to escape the trap of local optimality.

c.

to unrecord forbidden moves, which are referred to as tabu moves .

d.

all of the above

Discuss
Answer: (b).to escape the trap of local optimality.
Page 4 of 4

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