set-1

1. Intelligence is defined as: ______

  1. The capacity to acquire and apply knowledge.

  2. The faculty of thought and reason.

  3. Superior powers of mind.

  4. All of mentioned above

Show me the answer

Answer: 4. All of mentioned above

Explanation:

  • Intelligence involves the ability to acquire knowledge, think, reason, and solve problems.

  • It also includes superior mental capabilities and the ability to apply knowledge in various situations.

2. Artificial Intelligence (AI) is the simulation of human intelligence by machines. AI has ability to ______

  1. Solve Problems

  2. Act Rationally

  3. Act like Humans

  4. All of mentioned above

Show me the answer

Answer: 4. All of mentioned above

Explanation:

  • AI is designed to mimic human intelligence, which includes problem-solving, rational decision-making, and acting in ways that resemble human behavior.

  • These abilities collectively define the scope of AI.

3. The central principle of AI includes ______

  1. Reasoning, knowledge, planning, learning and communication

  2. Perception and the ability to move and manipulate objects.

  3. It is the science and engineering of making intelligent machines, especially intelligent computer programs

  4. All of the mentioned above

Show me the answer

Answer: 4. All of the mentioned above

Explanation:

  • AI involves reasoning, knowledge representation, planning, learning, and communication.

  • It also includes perception and the ability to interact with the environment.

  • These principles collectively form the foundation of AI.

4. ______ is about AI

  1. Making a machine Intelligent

  2. Putting your intelligence in Machine

  3. Programming on Machine with your Own Intelligence

  4. Playing a game on Computer

Show me the answer

Answer: 1. Making a machine Intelligent

Explanation:

  • AI focuses on creating systems that can perform tasks that typically require human intelligence, such as learning, reasoning, and problem-solving.

  • The goal is to make machines intelligent, not to transfer human intelligence into machines.

5. What is Artificial Intelligence?

  1. Artificial Intelligence is a field that aims to make humans more intelligent

  2. Artificial Intelligence is a field that aims to collect and mine the data

  3. Artificial Intelligence is a field that aims to develop intelligent machines

  4. Artificial Intelligence is a field that aims to improve the privacy and security

Show me the answer

Answer: 3. Artificial Intelligence is a field that aims to develop intelligent machines

Explanation:

  • AI is a branch of computer science that focuses on creating machines capable of performing tasks that require human intelligence.

  • The primary goal is to develop intelligent machines, not to enhance human intelligence or focus solely on data mining or security.

6. ______ is the father of Artificial Intelligence

  1. Alan Turing

  2. John McCarthy

  3. Lady ADA

  4. Charles Babbage

Show me the answer

Answer: 2. John McCarthy

Explanation:

  • John McCarthy is widely recognized as the father of Artificial Intelligence.

  • He coined the term "Artificial Intelligence" in 1956 and made significant contributions to the field.

7. If a machine can change its course of action based on the external environment on its own, the machine is called ______

  1. Ideal

  2. Intelligent

  3. Both A and B

  4. Mobile

Show me the answer

Answer: 2. Intelligent

Explanation:

  • An intelligent machine can adapt its behavior based on changes in the environment.

  • This ability to learn and make decisions autonomously is a hallmark of intelligence.

8. ______ is the branch of Artificial Intelligence.

  1. Network Architecture

  2. Full Stack Developer

  3. Machine Learning

  4. None of above

Show me the answer

Answer: 3. Machine Learning

Explanation:

  • Machine Learning is a subset of AI that focuses on the development of algorithms that allow computers to learn from and make predictions based on data.

  • It is one of the core branches of AI.

9. ______ is the goal of an AI

  1. To extract scientific causes

  2. To solve artificial problems

  3. To solve real-world problems

  4. To explain various sorts of intelligence

Show me the answer

Answer: 3. To solve real-world problems

Explanation:

  • The primary goal of AI is to develop systems that can solve real-world problems efficiently.

  • AI aims to mimic human intelligence to address practical challenges.

10. ______ is an application of AI

  1. It helps to exploit vulnerabilities to secure the firm

  2. Easy to create a website

  3. It helps to deploy applications on the cloud

  4. Language understanding and problem-solving (Text analytics and NLP)

Show me the answer

Answer: 4. Language understanding and problem-solving (Text analytics and NLP)

Explanation:

  • Natural Language Processing (NLP) is a key application of AI that involves understanding and generating human language.

  • NLP enables machines to interact with humans in a natural way, solving problems related to language understanding.

11. In how many categories process of Artificial Intelligence is categorized?

  1. Processes are categorized based on the provided input and gained output.

  2. Categorized into 3 categories

  3. Categorized into 4 categories

  4. Process is not categorized

Show me the answer

Answer: 2. Categorized into 3 categories

Explanation:

  • The processes in AI are generally categorized into 3 main types: supervised learning, unsupervised learning, and reinforcement learning.

  • These categories are based on how the AI system learns from data.

12. Based on ______ parameter Artificial Intelligence is categorized.

  1. Functionality

  2. Durability

  3. Capability

  4. Both A and C

Show me the answer

Answer: 4. Both A and C

Explanation:

  • AI is categorized based on functionality (e.g., reactive machines, limited memory, theory of mind, self-awareness).

  • It is also categorized based on capability (e.g., narrow AI, general AI, super AI).

13. ______ is not an application of artificial intelligence

  1. Computer Vision

  2. Natural Language Processing

  3. Containerization

  4. Image Recognition

Show me the answer

Answer: 3. Containerization

Explanation:

  • Containerization is a technology used in software development and deployment, such as Docker.

  • It is not directly related to AI, unlike computer vision, NLP, and image recognition.

14. ______ is the challenges of AI

  1. Black box problem

  2. AI Algorithm Bias

  3. High computing power requirement

  4. All of the mentioned above

Show me the answer

Answer: 4. All of the mentioned above

Explanation:

  • AI faces several challenges, including the black box problem (lack of transparency in decision-making).

  • Algorithm bias (biased outcomes due to biased data).

  • High computing power requirements for training and running AI models.

15. Consider the statement “AI will take over the jobs” is this statement true or its just a myth?

  1. Myth

  2. Fact

  3. May be myth of Fact

  4. Neither myth not fact

Show me the answer

Answer: 1. Myth

Explanation:

  • While AI will automate certain tasks, it is unlikely to completely take over jobs.

  • Instead, it will transform the nature of work, creating new opportunities and requiring humans to adapt.

16. ______ is the opensource Open-source AI software.

  1. Acumos AI

  2. ClearML

  3. H2O.ai

  4. All of mentioned above

Show me the answer

Answer: 4. All of mentioned above

Explanation:

  • Acumos AI, ClearML, and H2O.ai are all open-source AI platforms.

  • They provide tools for developing and deploying AI models.

17. Which of the given language is not commonly used for AI?

  1. LISP

  2. PROLOG

  3. Python

  4. PHP

Show me the answer

Answer: 4. PHP

Explanation:

  • LISP, PROLOG, and Python are commonly used in AI development.

  • PHP is primarily used for web development and is not commonly associated with AI.

18. An ______ is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators.

  1. Agent

  2. Re-agent

  3. Perceptor

  4. Robotic arm

Show me the answer

Answer: 1. Agent

Explanation:

  • An agent in AI is an entity that perceives its environment through sensors and acts upon it through actuators to achieve specific goals.

  • This definition aligns with the concept of an intelligent agent.

19. ______ maps from percept histories to actions: f:P∗→Af: P^* \rightarrow A

  1. Perceptor function

  2. Agent function

  3. Sensor function

  4. Actuator function

Show me the answer

Answer: 2. Agent function

Explanation:

  • The agent function maps percept histories (sequences of percepts) to actions.

  • This function defines the behavior of the agent based on its perception of the environment.

20. The ______ runs on the physical architecture to produce ‘f’ in this relation f:P∗→Af: P^* \rightarrow A

  1. Actuator Program

  2. Environment Program

  3. Rational Program

  4. Agent Program

Show me the answer

Answer: 4. Agent Program

Explanation:

  • The agent program runs on the physical architecture to implement the agent function f:P∗→Af: P^* \rightarrow A.

  • It determines how the agent behaves based on its percepts.

21. A ______ should select an action that is expected to maximize its performance measure, based on the evidence provided by the percept sequence and whatever built-in knowledge the agent has.

  1. Agent

  2. Rational Agent

  3. Irrational Agent

  4. Environment

Show me the answer

Answer: 2. Rational Agent

Explanation:

  • A rational agent selects actions that maximize its performance measure.

  • It uses percept sequences and built-in knowledge to make optimal decisions.

22. What is an ‘agent’?

  1. Perceives its environment through sensors and acting upon that environment through actuators

  2. Takes input from the surroundings and uses its intelligence and performs the desired operations

  3. A embedded program controlling line following robot

  4. All of the mentioned

Show me the answer

Answer: 4. All of the mentioned

Explanation:

  • An agent perceives its environment through sensors and acts upon it through actuators.

  • It uses intelligence to perform operations and can be implemented as an embedded program, such as in a line-following robot.

23. Agents behavior can be best described by ______.

  1. Perception sequence

  2. Environment in which agent is performing

  3. Sensors and Actuators

  4. Agent function

Show me the answer

Answer: 4. Agent function

Explanation:

  • The behavior of an agent is best described by its agent function, which maps percept sequences to actions.

  • This function defines how the agent responds to its environment.

24. An agent is composed of ___/Agent’s structure can be viewed as ___

  1. Architecture

  2. Agent Function

  3. Perception Sequence

  4. Architecture and Program

Show me the answer

Answer: 4. Architecture and Program

Explanation:

  • An agent is composed of both architecture (the physical hardware) and program (the software that implements the agent function).

  • Together, they define the agent's structure and behavior.

25. A rational agent is an agent that forever does the right thing.

  1. True

  2. False

  3. Partially true

  4. Completely false

Show me the answer

Answer: 1. True

Explanation:

  • A rational agent is designed to always select actions that maximize its performance measure.

  • It consistently does the "right thing" based on its knowledge and percepts.

26. Performance Measures are not fixed for all agents.

  1. True

  2. False

  3. Partially true

  4. Completely false

Show me the answer

Answer: 1. True

Explanation:

  • Performance measures vary depending on the agent's goals and environment.

  • Different agents may have different criteria for success.

27. The Task Environment of an agent consists of which of the following?

  1. Sensors

  2. Performance Measures

  3. Actuators

  4. All of these

Show me the answer

Answer: 4. All of these

Explanation:

  • The task environment includes sensors, performance measures, and actuators.

  • These components define how the agent interacts with and evaluates its environment.

28. ______ following is rational at any given time depends on

  1. The actions that the agent can do

  2. The agent’s previous knowledge of the environment

  3. The performance measure that describes the criterion of success

  4. All of these

Show me the answer

Answer: 4. All of these

Explanation:

  • Rationality depends on the agent's possible actions, its knowledge of the environment, and the performance measure.

  • These factors collectively determine the agent's decision-making process.

29. ______ is the act of task environment and Rational Agents in AI?

  1. Observation and Solution

  2. Problem and Solution

  3. Problem and Observation

  4. Identification and Observation

Show me the answer

Answer: 2. Problem and Solution

Explanation:

  • The task environment and rational agents in AI involve identifying problems and finding solutions.

  • Rational agents aim to solve problems within their environment.

30. PEAS Stands for ______ in task Environment.

  1. Prediction, Environment, Augmentation, Sensors

  2. Perceiving, Entertainment, Actuators, Sense

  3. Performance, Environment, Actuators, Sensors

  4. Performance, Evolvement, Actuators, Sense

Show me the answer

Answer: 3. Performance, Environment, Actuators, Sensors

Explanation:

  • PEAS stands for Performance, Environment, Actuators, Sensors.

  • It is a framework used to define the task environment of an agent.

31. ______ is used to select a particular environment when we want to run the agent

  1. Environment creator

  2. Environment Generator

  3. Both A & B

  4. None of these

Show me the answer

Answer: 2. Environment Generator

Explanation:

  • An environment generator is used to create or select a specific environment for the agent to operate in.

  • It allows for controlled testing and simulation of the agent's behavior.

32. Consider an Agent “Taxi Driver” What might be the Performance Measure for it?

  1. Comfortable trip

  2. Roads

  3. Steering Wheels

  4. Cameras

Show me the answer

Answer: 1. Comfortable trip

Explanation:

  • For a taxi driver agent, the performance measure would likely focus on providing a comfortable and efficient trip for passengers.

  • Other options like roads, steering wheels, and cameras are part of the environment, not the performance measure.

33. Consider an Agent “Medical Diagnosis System” What might be the Environments of it?

  1. Healthy Patients

  2. Patients

  3. Hospital

  4. Both B and C

Show me the answer

Answer: 4. Both B and C

Explanation:

  • The environment for a medical diagnosis system includes patients and the hospital setting.

  • These are the contexts in which the system operates.

34. Consider an Agent “Part-picking Robot” What might be the sensors of it?

  1. Bins

  2. Joined Arms and Hands

  3. Camera

  4. None of the above

Show me the answer

Answer: 3. Camera

Explanation:

  • A part-picking robot would likely use cameras as sensors to identify and locate parts.

  • Bins and arms are part of the robot's physical structure, not sensors.

35. ______ types of observing environments are there in AI.

  1. 1

  2. 4

  3. 2

  4. 3

Show me the answer

Answer: 3. 2

Explanation:

  • There are two types of observing environments in AI: fully observable and partially observable.

  • This classification depends on whether the agent can perceive the entire state of the environment.

36. There are ______ basic types/structures of Agents in AI.

  1. 3

  2. 5

  3. 6

  4. 7

Show me the answer

Answer: 2. 5

Explanation:

  • There are five basic types of agents in AI: simple reflex agents, model-based reflex agents, goal-based agents, utility-based agents, and learning agents.

  • These types differ in their complexity and decision-making processes.

37. Name the type of the agent shown below:

Agent

KNOWLEDGE

LOOK-UP TABLE Key value Percept1 action1 Percept2 action2 ...

Sensors

What the world is like now

What action I should do now

Actuators

Environment

  1. Simple reflex agent

  2. Model-based agent

  3. Goal-based agent

  4. Table driven agent

Show me the answer

Answer: 4. Table driven agent

Explanation:

  • The agent uses a look-up table to map percepts to actions, which is characteristic of a table-driven agent.

  • This type of agent relies on pre-defined mappings rather than complex reasoning.

38. Name the type of the agent shown below:

Agent

Condition-action rules

Sensors

What the world is like now

What action I should do now

Actuators

Environment

  1. Simple reflex agent

  2. Model-based reflect agent

  3. Goal-based agent

  4. Table driven agent

Show me the answer

Answer: 1. Simple reflex agent

Explanation:

  • The agent uses condition-action rules to directly map percepts to actions, which is characteristic of a simple reflex agent.

  • This type of agent does not maintain an internal model of the world.

39. Name the type of the agent shown below

State How the world evolves What my actions do Condition-action rules What the world is like now What action I should do now

Agent Actuators

  1. Simple reflex agent

  2. Model-based reflect agent

  3. Goal-based agent

  4. Table driven agent

Show me the answer

Answer: 2. Model-based reflect agent

Explanation:

  • The agent maintains an internal state and uses it to track how the world evolves, which is characteristic of a model-based reflex agent.

  • This type of agent can handle partially observable environments.

40. Name the type of the agent shown below:

State How the world evolves What my actions do What it will be like if I do action A What the world is like now What action I should do now

Agent Goals Actuators

  1. Simple reflex agent

  2. Model-based reflect agent

  3. Goal-based agent

  4. Learning agents

Show me the answer

Answer: 3. Goal-based agent

Explanation:

  • The agent considers goals and evaluates the outcomes of its actions, which is characteristic of a goal-based agent.

  • This type of agent aims to achieve specific objectives.

41. Name the type of the agent shown below:

State How the world evolves What my actions do

Sensors What the world is like now What it will be like if I do action A How happy I will be in such a state What action I should do now

Utility Agent

Actuators

  1. Utility-based agent

  2. Model-based reflect agent

  3. Goal-based agent

  4. Learning agents

Show me the answer

Answer: 1. Utility-based agent

Explanation:

  • The agent evaluates actions based on a utility function, which measures how "happy" it will be in a given state.

  • This is characteristic of a utility-based agent.

42. Name the type of the agent shown below:

Performance standard

Critic feedback Learning element learning goals Problem generator Acquiring knowledge Personnel Environment Action Actions

  1. Utility-based agent

  2. Model-based reflect agent

  3. Goal-based agent

  4. Learning agents

Show me the answer

Answer: 4. Learning agents

Explanation:

  • The agent includes a learning element and a critic to improve its performance over time, which is characteristic of a learning agent.

  • This type of agent adapts based on feedback and experience.

43. Which agent deals with happy and unhappy states?

  1. Simple reflex agent

  2. Goal based agent

  3. Table driven agent

  4. Utility based agent

Show me the answer

Answer: 4. Utility based agent

Explanation:

  • A utility-based agent evaluates states based on a utility function, which measures how "happy" or "unhappy" the agent is in a given state.

  • This allows the agent to make decisions that maximize its overall happiness.

44. In which agent does the problem generator is present?

  1. Observing agent

  2. Reflex agent

  3. Learning agent

  4. Simple agent

Show me the answer

Answer: 3. Learning agent

Explanation:

  • A learning agent includes a problem generator to explore new actions and improve its performance over time.

  • This component helps the agent learn from its environment.

45. What is the rule of simple reflex agent?

  1. Simple-action rule

  2. Condition-action rule

  3. Both Simple & Condition-action rule

  4. Utility rules

Show me the answer

Answer: 2. Condition-action rule

Explanation:

  • A simple reflex agent operates using condition-action rules, which directly map percepts to actions.

  • These rules are pre-defined and do not involve complex reasoning.

46. The action of the Simple reflex agent completely depends upon ______.

  1. Perception history

  2. Current perception

  3. Performance measures

  4. Goal functions

Show me the answer

Answer: 2. Current perception

Explanation:

  • A simple reflex agent bases its actions solely on the current perception of the environment.

  • It does not consider past perceptions or future consequences.

47. ______ kind of agent architecture should an agent can use.

  1. Relaxed

  2. Relational

  3. Both A and B

  4. None of Above

Show me the answer

Answer: 3. Both A and B

Explanation:

  • An agent can use both relaxed and relational architectures depending on the task and environment.

  • These architectures provide flexibility in how the agent processes information and makes decisions.

48. An agent’s sensors give it access to complete state of the environment at each point in time, then we say that the task environment is ______.

  1. Partially observable

  2. Fully observable

  3. Static

  4. Deterministic

Show me the answer

Answer: 2. Fully observable

Explanation:

  • If an agent's sensors provide complete access to the environment's state at all times, the environment is fully observable.

  • This means the agent has all the information it needs to make decisions.

49. Consider an example of a Chess game, in which a player gets to see the whole board. Which environment is this?

  1. Partially observable

  2. Fully observable

  3. Static

  4. Deterministic

Show me the answer

Answer: 2. Fully observable

Explanation:

  • In a chess game, the player can see the entire board, making the environment fully observable.

  • The player has complete information about the game state at all times.

50. Consider an example of poker game, in which a player gets to see only his cards. Which environment is this?

  1. Partially observable

  2. Fully observable

  3. Static

  4. Deterministic

Show me the answer

Answer: 1. Partially observable

Explanation:

  • In a poker game, a player can only see their own cards, making the environment partially observable.

  • The player does not have complete information about the game state.

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