Artificial Intelligence Questions & Answers – Online Search Agent

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This set of Artificial Intelligence Multiple Choice Questions & Answers (MCQs) focuses on “Online Search Agent”.

1. Which search agent operates by interleaving computation and action?
a) Offline search
b) Online search
c) Breadth-first search
d) Depth-first search
View Answer

Answer: b
Explanation: In online search, it will first take an action and then observes the environment.
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2. What is called an exploration problem?
a) State and actions are unknown to the agent
b) State and actions are known to the agent
c) Only actions are known to agent
d) None of the mentioned
View Answer

Answer: a
Explanation: Online search is a necessary idea for an exploration problem where the states and actions are unknown to the agent.

3. Which are necessary for an agent to solve an online search problem?
a) Actions
b) Step-cost function
c) Goal-test
d) All of the mentioned
View Answer

Answer: d
Explanation: An online search problem can be solved by an agent executing actions, So these functions are necessary.
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4. When do we call the states are safely explorable?
a) A goal state is unreachable from any state
b) A goal state is denied access
c) A goal state is reachable from every state
d) None of the mentioned
View Answer

Answer: c
Explanation: None.

5. In which state spaces does the online-dfs-agent will work?
a) Irreversible state spaces
b) Reversible state spaces
c) Searchable state spaces
d) All of the mentioned
View Answer

Answer: b
Explanation: Online-DFS-Agent will work only state spaces where the actions are reversible.
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6. Which of the following algorithm is online search algorithm?
a) Breadth-first search algorithm
b) Depth-first search algorithm
c) Hill-climbing search algorithm
d) None of the mentioned
View Answer

Answer: c
Explanation: Hill-climbing search algorithm will have only current state in memory, So it is an online search algorithm.

7. Which search algorithm will use limited amount of memory?
a) RBFS
b) SMA*
c) Hill-climbing search algorithm
d) Both RBFS & SMA*
View Answer

Answer: d
Explanation: RBFE and SMA* will solve any kind of problem that A* can’t by using limited amount of memory.
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8. What is meant by simulated annealing in artificial intelligence?
a) Returns an optimal solution when there is a proper cooling schedule
b) Returns an optimal solution when there is no proper cooling schedule
c) It will not return an optimal solution when there is a proper cooling schedule
d) None of the mentioned
View Answer

Answer: a
Explanation: None.

9. How the new states are generated in genetic algorithm?
a) Composition
b) Mutation
c) Cross-over
d) Both Mutation & Cross-over
View Answer

Answer: d
Explanation: New states are generated by mutation and by crossover, which combines a pair of states from the population.
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10. Which method is effective for escaping from local minima?
a) Updating heuristic estimate
b) Reducing heuristic estimate
c) Eliminating heuristic estimate
d) None of the mentioned
View Answer

Answer: a
Explanation: Updating heuristic estimates from experience provides an effective method to escape from local minima.

Sanfoundry Global Education & Learning Series – Artificial Intelligence.

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Manish Bhojasia - Founder & CTO at Sanfoundry
Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He lives in Bangalore, and focuses on development of Linux Kernel, SAN Technologies, Advanced C, Data Structures & Alogrithms. Stay connected with him at LinkedIn.

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