Artificial Intelligence MCQs

Page No. 23

Greedy search strategy chooses the node for expansion in ___________


a Shallowest

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bDeepest

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cThe one closest to the goal node

✓


dMinimum heuristic cost

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Heuristic function h(n) is ________


aLowest path cost

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bCheapest path from root to goal node

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cEstimated cost of cheapest path from root to goal node

✓


d Average path cost

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The name “best-first search” is a venerable but inaccurate one. After all, if we could really expand the best node first, it would not be a search at all; it would be a straight march to the goal. All we can do is choose the node that appears to be best according to the evaluation function.


aTrue

✓


bFalse

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cA & B

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dNone of these

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View Answer True

Best-First search can be implemented using the following data structure.


aQueue

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bStack

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cPriority Queue

✓


dCircular Queue

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View Answer Priority Queue

Best-First search is a type of informed search, which uses ________________ to choose the best next node for expansion.


aEvaluation function returning lowest evaluation

✓


b Evaluation function returning highest evaluation

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cEvaluation function returning lowest & highest evaluation

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d None of them is applicable

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Uninformed search strategies are better than informed search strategies.


a True

✓


bFalse

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cA & B

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dNone of these

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View Answer True

The search strategy the uses a problem specific knowledge is known as ___________


aInformed Search

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bBest First Search

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cHeuristic Search

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dAll of the mentioned

✓


View Answer All of the mentioned

A* algorithm is based on ___________


aBreadth-First-Search

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bDepth-First –Search

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cBest-First-Search

✓


dHill climbing

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View Answer Best-First-Search

Searching using query on Internet is, use of ___________ type of agent.


aOffline agent

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bOnline agent

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cBoth Offline & Online agent

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d Goal Based & Online agent

✓



What are the two main features of Genetic Algorithm?


a Fitness function & Crossover techniques

✓


b Crossover techniques & Random mutation

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c Individuals among the population & Random mutation

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dRandom mutation & Fitness function

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