Artificial Intelligence MCQ (Multiple Choice Questions) - SchoolingAxis

Artificial Intelligence MCQ (Multiple Choice Questions)

 Que- Rational agent is the one who always does the right thing. State true or false 

a. TRUE 

b. False  

c. Nothing can be said 

d. None of the mentioned 


Ans- TRUE  


Que- Performance Measures are fixed for all agents. State true or false 

a. TRUE 

b. False  

c. Nothing can be said 

d. None of the mentioned 


Ans- TRUE  


Que- What is rational at any given time depends on 

a. The performance measure that defines the criterion of success 

b. The agent's prior knowledge of the environment 

c. The actions that the agent can perform 

d. All of the mentioned  


Ans- All of the mentioned   


Que- An omniscient agent knows the actual outcome of its actions and can act accordingly; but omniscience is impossible in reality. Rational Agent always does the right thing; but Rationality is possible in reality. State true or false 

a. TRUE 

b. False  

c. Nothing can be said 

d. None of the mentioned 


Ans- TRUE  


Que- The Task Environment of an agent consists of 

a. Sensors 

b. Actuators 

c. Performance Measures 

d. All of the mentioned  


Ans- All of the mentioned   


Que- What could possibly be the environment of a Satellite Image Analysis System? 

a. Computers in space and earth 

b. Image categorization techniques 

c. Statistical data on image pixel intensity value and histograms 

d. All of the mentioned  


Ans- All of the mentioned   


Que- Categorize Crossword puzzle in Fully Observable / Partially Observable. 

a. Fully Observable 

b. partially Observable 

c. All of the mentioned 

d. None of the mentioned  


Ans- Fully Observable  


Que- The game of Poker is a single agent. 

a. TRUE 

b. False  

c. Nothing can be said 

d. None of the mentioned 


Ans- False   


Que- Satellite Image Analysis System is (Choose the one that is not applicable). 

a. Episodic 

b. Semi-Static 

c. Single agent 

d. Partially Observable  


Ans- Partially Observable   


Que- An agent is composed of ________ 

a. Architecture 

b. Agent Function 

c. Perception Sequence 

d. Architecture and Program  


Ans- Architecture and Program   


Que- Which search agent operates by interleaving computation and action? 

a. Offline search 

b. Online search 

c. Breadth-first search 

d. Depth-first search   


Ans- Online search  


Que- What is called as 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   


Ans- State and actions are unknown to the agent  


Que- 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   


Ans- All of the mentioned    


Que- 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   


Ans- A goal state is reachable from every state  


Que- 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   


Ans- Reversible state spaces  


Que- 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   


Ans- Hill-climbing search algorithm  


Que- Which search algorithm will use limited amount of memory? 

a. RBFS 

b. SMA* 

c. Hill-climbing search algorithm 

d. Both RBFS & SMA*   


Ans- Both RBFS & SMA*    


Que- 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   


Ans- Returns an optimal solution when there is a proper cooling schedule  


Que- How the new states are generated in genetic algorithm? 

a. Composition 

b. Mutation 

c. Cross-over 

d. Both Mutation & Cross-over   


Ans- Both Mutation & Cross-over    


Que- 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   


Ans- Updating heuristic estimate  


Que- Which depends on the percepts and actions available to the agent? 

a. Agent 

b. Sensor 

c. Design problem 

d. None of the mentioned   


Ans- Design problem  


Que- Which were built in such a way that humans had to supply the inputs and interpret the outputs? 

a. Agents 

b. AI system 

c. Sensor 

d. Actuators   


Ans- AI system  


Que- Which technology uses miniaturized accelerometers and gyroscopes? 

a. Sensors 

b. Actuators 

c. MEMS 

d. None of the mentioned   


Ans- MEMS  


Que- What is used for tracking uncertain events? 

a. Filtering algorithm 

b. Sensors 

c. Actuators 

d. None of the mentioned   


Ans- Filtering algorithm  


Que- What is not represented by using propositional logic? 

a. Objects 

b. Relations 

c. Both Objects & Relations 

d. None of the mentioned   


Ans- Both Objects & Relations  


Que- Which functions are used as preferences over state history? 

a. Award 

b. Reward 

c. Explicit 

d. Implicit   


Ans- Reward  


Que- Which kind of agent architecture should an agent an use? 

a. Relaxed 

b. Logic 

c. Relational 

d. All of the mentioned   


Ans- All of the mentioned    


Que- Specify the agent architecture name that is used to capture all kinds of actions. 

a. Complex 

b. Relational 

c. Hybrid 

d. None of the mentioned   


Ans- Hybrid  


Que- Which agent enables the deliberation about the computational entities and actions? 

a. Hybrid 

b. Reflective 

c. Relational 

d. None of the mentioned   


Ans- Reflective  


Que- What can operate over the joint state space? 

a. Decision-making algorithm 

b. Learning algorithm 

c. Complex algorithm 

d. Both Decision-making & Learning algorithm   


Ans- Both Decision-making & Learning algorithm    


Que- What is the action of task environment in artificial intelligence? 

a. Problem 

b. Solution 

c. Agent 

d. Observation   


Ans- Problem  


Que- What is the expansion if PEAS in task environment? 

a. Peer, Environment, Actuators, Sense 

b. Perceiving, Environment, Actuators, Sensors 

c. Performance, Environment, Actuators, Sensors 

d. None of the mentioned   


Ans- Performance, Environment, Actuators, Sensors  


Que- What kind of observing environments are present in artificial intelligence? 

a. Partial 

b. Fully 

c. Learning 

d. Both Partial & Fully   


Ans- Both Partial & Fully    


Que- What kind of environment is strategic in artificial intelligence? 

a. Deterministic 

b. Rational 

c. Partial 

d. Stochastic   


Ans- Deterministic  


Que- What kind of environment is crossword puzzle? 

a. Static 

b. Dynamic 

c. Semi Dynamic 

d. None of the mentioned   


Ans- Static  


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