# Artificial Intelligence and Robotics mcqs

## Robotics mcq questions and answers

1. Artificial Intelligent is

1. System to make machine intelligent
2. Computer to make machine intelligent
3. Study of algorithms to make machine intelligent
4. Study to create animation

System to make machine intelligent

2. Father of AI

1. John McCarthy
2. Alan Turing
3. Norbert Wiener
4. Newell and Simon

John McCarthy

3. What is a state space

1. The set of all states reachable from the initial state.
2. All goal states
3. All initial states
4. Reversible states

The set of all states reachable from the initial state.

4. What is goal Test?

1. It determines whether a given state is goal state.
2. It determines numeric cost of goal state.
3. It determine path from the initial to goal state.
4. All of the above

It determines whether a given state is goal state.

5. In, Hill Climbing Algorithm

1. We need to consider all nodes generated from initial node
2. We need to consider all nodes generated from current node
3. We need to consider all nodes generated from goal node

We need to consider all nodes generated from current node

6. Types of Hill Climbing Algorithm are

1. Simple hill Climbing
2. Steepest-Ascent hill-climbing
3. Stochastic hill Climbing
4. Startfast hill climbing

Simple hill Climbing
Steepest-Ascent hill-climbing
Stochastic hill Climbing

7. Termination criteria for Hill Climbing algorithm is

1. no successor of the node has a better heuristic value.
2. no successor of the node has a less heuristic value.

no successor of the node has a better heuristic value.

8. DFID means

1. Depth First Iterative deepening
2. Depth First Information Depended
3. Depth First Information Difference

Depth First Iterative deepening

9. DB-DFS stands for *

1. Depth Bind Depth First Search
2. Depth Bounded Depth First Search

Depth Bounded Depth First Search

10. In Goal Stack Planning, Robot arm can perform actions like

1. Unstack, Stack
2. Pikup, Putdown
3. Move and Generate

Unstack, Stack
Pikup, Putdown

## AIR mcq sppu

11. unstack (x,y) means

1. Pick up X from its current position on block Y.
2. Place block X on block Y.
3. Pick up X from the table and hold it

Pick up X from its current position on block Y.

12. For representation of STRIPS language we require

1. Goal State and Initial State
2. Actions
3. All of the above

All of the above

13. STRIPS Language Representation, we need to use

1. First order predicate
2. Second order predicate
3. None of the above

First order predicate

14. FSSP starts with

1. goal state and try to find initial state
2. initial state and try to find goal state
3. None of the above

initial state and try to find goal state

15. Stack (x,y) means

1. Pick up X from its current position on block Y.
2. Place block X on block Y.
3. Pick up X from the table and hold it.

Place block X on block Y.

16. In order to solve a problem represented by AND node,

1. you need to solve the problems represented by all of his children
2. you need to solve the problems represented by any one of his children
3. you need to solve the problems represented by any two of his children

you need to solve the problems represented by all of his children

## Artificial Intelligence and Robotics mcqs

17. In order to solve a problem represented by OR node,

1. you need to solve the problems represented by all of his children
2. you need to solve the problems represented by any one of his children
3. you need to solve the problems represented by any two of his children

you need to solve the problems represented by any one of his children

18. In Rule based system, rules represented in the form of

1. Pattern -> Action
2. Action -> Pattern

Pattern -> Action

19. OPS5 stands for

1. Official Production System
2. Official Produce System
3. Office Production System

Official Production System

## Artificial Intelligence and Robotics mcqs questions

20. Types of Localization

1. Global and Local Localization
2. Strong and Week Localization

Strong and Week Localization

21. Landmark Classes are

1. active or passive
2. natural or artificial
3. Sound navigate and range

active or passive

22. Trilateration refers to

1. the use of distance contraints
2. the use of angle (orientation) constraints.
3. the use of free space

the use of distance contraints

23. What is Delivery Robots?

A delivery robot is an automated robot that brings your delivery directly to your door.

24. Triangulation refers to

1. the use of angle (orientation) constraints.
2. the use of variable constraints.

the use of angle (orientation) constraints.

25. Mapping Techniques are

1. Sensorial
2. Topological
3. Geometric
4. All of above

All of above

26. Metric maps

1. which are based on an absolute reference frame and numerical estimates of where objects are in space
2. which are based on an absolute variable frame

which are based on an absolute reference frame and numerical estimates of where objects are in space

27. Topological maps also known as

1. relational maps
2. topological maps
3. sensors maps

relational maps

28. Robotics deals with

1. the construction, use of robots and computer systems
2. the design, use of robots and computer systems
3. the operation, use of robots and computer systems
4. All of the above

All of the above

29. Components of robotics are

1. power source
2. collection of sensors
3. communication hardware
4. all of the above

all of the above

30. Which is Path Planning algorithm

1. Bug2 Algorithm
2. Point to algorithm
3. Bug_P algorithm

Bug2 Algorithm

31. Bug2 Algorithm is

1. from the class of bug algorithms.
2. from the class of bug-free algorithms.
3. from the class of bug-miss algorithms.

from the class of bug algorithms.

32. Range Sensors returns infinity if â€¦â€¦â€¦â€¦â€¦â€¦â€¦ exists in that direction

1. no obstacle
2. obstacle
3. free space

obstacle

33. Sonar sensor stands for

2. Sound navigate and ranging
3. Sound navigate and range

34. Laser rangefinders are based on methodologies like

1. Triangulation
2. Time of flight (TOF)
3. Phase-based
4. all of above

all of above

3. Ratio detecting and raining

36. Sensory-based behavior divided into two basic classes

1. tropism and taxis
2. tropism and axis
3. tropism and terms

tropism and taxis

37. Knowledge based agent used

2. Tell and remove interface
3. Remove and solve interface

38. Inputs for Inference engine are

1. Knowledge base
2. Input from environment
3. Query
4. All of above

All of above

39. Compound Proposition means

1. A statement formed from one or more atomic propositions using logical connectives.
2. A statement that does not specifically contain sub statements

A statement formed from one or more atomic propositions using logical connectives.

40. We can use quantifiers in â€¦â€¦â€¦.

1. Propositional logic
2. Predicate logic
3. First order logic
4. both 2 and 3

both 2 and 3

41. Types of quantifiers are

1. Universal
2. Existential
3. All of the above

All of the above

42. Unification algorithm used to find *

1. Quantifiers
2. Unifier
3. Rule

Unifier

43. In unification algorithm, if two predicate expressions having same
â€¦â€¦â€¦â€¦â€¦â€¦then only we can find unifier

1. Initial Predicate symbol
2. No of arguments
3. All of above

Initial Predicate symbol

44. Unifier means

1. Substitution so that two predicate expression will be identical.
2. Addition so that two predicate expression will be identical.
3. All of the above

Substitution so that two predicate expression will be identical.

45. FOL Stands for

1. First office order
2. First order logic
3. Firstly order logic

First order logic

46. In ontology, we need to consider

1. Object and Categories
2. Unifier
3. Rule

Unifier

47. First step of NLP is

1. Lexical Analysis
2. Symantec Analysis
3. Syntactic Analysis

Lexical Analysis

48. NLP stands for

1. Natural Language Processing
2. Neutral Language processing

Natural Language Processing

49. Pragmatic analysis means

1. It involves deriving those aspects of language which require real world knowledge.
2. It draws the exact meaning or the dictionary meaning from the text.
3. It involves identifying and analyzing the structure of words.

It involves deriving those aspects of language which require real world knowledge.

50. The â€¦â€¦â€¦â€¦.is the basic information processing unit of a NN

1. neuron
2. Bias
3. Network

neuron

51. Back propagation used to

1. modify weights to minimize errors
2. modify weights to maximize errors
3. modify algorithm to minimize errors

modify weights to minimize errors

52. Calculation of error in backpropagation

1. ErrorB= Actual Output â€“ Desired Output
2. ErrorB= Desired Output â€“ Actual Output

ErrorB= Actual Output â€“ Desired Output

1. Backpropagation can be quite sensitive to noisy data.
2. It has no parameters to tune apart from the numbers of input.
3. It is a standard method that generally works well.

Backpropagation can be quite sensitive to noisy data.

54. Types of Machine learning are

1. Reinforcement Learning
2. Supervised Learning
3. Unsupervised Learning
4. All of the above

All of the above

55. In supervised Learning,â€¦â€¦â€¦â€¦â€¦â€¦â€¦.will be used

1. Labeled data
2. Unlabeled data
3. missing data

Labeled data

56. In unsupervised Learning,â€¦â€¦â€¦â€¦â€¦â€¦â€¦.will be used

1. Labeled data
2. Unlabeled data
3. missing data