Artificial Intelligence MCQs On AI introduction, What is AI, Foundations of AI, History of AI, Problem Solving, Searching for Solutions, Types of Search Strategies, Uninformed Search, Breadth-First Search, Depth-First Search, Iterative Deepening, Functions, Local Search Algorithms and Optimization Problems, Adversarial Search: Minmax Algo, Alpha Beta Pruning, Introduction to Reasoning and Knowledge Representation, Propositional Logic, Rules of Inferences, First Order logic.
Syntax and semantics, Inference in first-order logic, Forward and Backward chaining, Resolution, Uncertainty, and Reasoning Bayes’ Theorem, Decision Making, Decision Network, Supervised and Unsupervised, Classification, Clustering, Decision Tree, Introduction to Prolog
Artificial Intelligence MCQs
1. Who is the father of AI?
A. Karl Peason
B. John Mccarthy
C. Mark
D. James Gosling
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2. Artificial Intelligence Introduce In?
A. 1956
B. 1965
C. 1962
D. 1955
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3. Machine Learning Is Introduced In?
A. 1959
B. 1956
C. 1969
D. 1965
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4. Formula Of A* Algorithm Is.
A. F(N)=G(N) + H(N)
B. F(N)=G(N) – H(N)
C. F(N)=G(N) / H(N)
D. F(N)=G(N) * H(N)
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5. 8- Puzzle Problem Without Heuristic Vales Are Also Called?
A. Uninformed Search
B. Informed Search
C. Bubble Sort
D. Binary Search
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6. 8- Puzzle Problem With Heuristic Vales Are Also Called?
A. Uninformed Search
B. Informed Search
C. Bubble Sort
D. Binary Search
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7. The Science And Engineering Of Making Intelligent Machines Called?
A. Ai
B. Machine Learning
C. Deep Learning
D. Data Mining
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8. Python Developed In ?
A. 1989
B. 1998
C. 1997
D. 1979
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9. Google Recommendations Are Called?
A. Ai
B. Machine Learning
C. Data Mining
D. Data Where Housing
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10. Python Was Created By?
A. Guido Rossum
B. Arthur Samuel
C. John Mccarthy
D. James Gosling
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11. Encounter Some Missing Values, Corrupted Data, And Remove Unnecessary Data Called?
A. Data Mining
B. Data Cleaning
C. Redundancy Control
D. Data Where Housing
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12. Clustering Is A Problem Of?
A. Regression
B. Classification
C. Un-Supervised Learning
D. Reinforcement
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13. Whose Machine Learning Type Is Based On Reward?
A. Supervised Learning
B. Reinforcement
C. A & B Both
D. Un-Supervised Learning
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14. Robot’s “Arm” Is Called?
A. Actuator
B. Effector
C. Manipulator
D. Sensors
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15. The Conference That Launches The Ai Revolution Was Held In?
A. Harvard
B. Dartmouth
C. New York
D. London
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16. What Is Ai ?
A. Playing Games
B. Programming With Your Own Intelligence
C. Making Machines Intelligent
D. Solve Problems
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17. Algorithm Is A Supervised Learning Method For Multilayer Perceptron?
A. Back Propagation
B. Classification
C. Clustering
D. Grouping
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18. The Process Of Deriving Meaningful Information From A Lot of Data Is Called?
A. Extraction
B. Data Mining
C. Data Where Housing
D. Abstraction
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19. NLP Stands For?
A. Neural Language Processing
B. Natural Language Processing
C. Network Language Processing
D. None Linear Problem
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20. The Process Of Splitting The Whole Data Into Smaller Chunks Called?
A. Splitting
B. Tokenization
C. Sorting
D. Division
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21. Normalize Words Into Its Base Form Or Root Form?
A. Spanning
B. Stemming
C. Sorting
D. Normalization
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22. To Overcome The Limitation Of Stemming —— Is Used ?
A. Lemmatization
B. Normalization
C. Erosion
D. Spanning
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23. A Set Of Commonly Used Words In Any Language, Not Just English ?
A. Higher Language
B. Stop Words
C. Predefine Words
D. Common Words
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24. In Which Conference John Mccarthy First Coined The Term “Artificial Intelligence” In 1956 ?
A. Dartmouth Conference.
B. Acm Conference
C. Aaai Conference
D. Aaai Conference
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25. Which Programming Language Is Best Choice For Development Of Ai ?
A. Python
B. Java
C. Dot .Net
D. Mat-Lab
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27. There Are How Many Steps In Machine Learning To Solve A Problem ?
A. 3 Steps
B. 5 Steps
C. 7 Steps
D. 9 Steps
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28. In Supervised Learning There Is Given ?
A. Both Inputs & Outputs
B. Only Inputs
C. Only Outputs
D. None
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29. In Unsupervised Learning There Is Given.
A. Both Inputs & Outputs
B. Only Inputs
C. Only Outputs
D. None
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30. In Supervised Learning Type Of Data Is.
A. Labeled Data
B. Unlabeled Data
C. Both
D. None
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31. In Unsupervised Learning Type Of Data Is.
A. Labeled Data
B. Unlabeled Data
C. Both
D. None
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32. Which Algorithm Is Example Of Supervised Learning ?
A. K-Nearest Neighbors
B. K-Means
C. Both
D. None
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33. Which Algorithm Is Example Of Unsupervised Learning ?
A. K-Means
B. K-Nearest Neighbors
C. Both
D. None
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34. What Is Date The Birth Of Ai ?
A. 1958
B. 1965
C. 1956
D. 1959
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35. What Is The Name Of First Research Lab For Ai ?
A. Allen Institute Of Ai
B. Robotics Laboratory
C. First Al Laboratory
D. Turing Institute
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36. In Which Year First Ai Research Lab Developed ?
A. 1956
B. 1959
C. 1965
D. 1960
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37. First Robot Was Introduced To General Motors Assembly Line In ?
A. 1960
B. 1959
C. 1965
D. 1956
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38. First Robot Was Introduced In 1960 To Which Assembly Line ?
A. Ai Laboratory
B. General Motor’s Assembly Line
C. Allen Institute Of Ai
D. Turing Institute
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39. The First Al Chat-Bot Name Which Introduced In 1961 ?
A. Alexa
B. Siri
C. Eliza
D. Cortana
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40. Who Won 2005 Darpa Grand Challenge ?
A. Stanford Team
B. Red Team
C. Team Gray
D. Team Terramax
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41. When Was Developed Ibm Watson ?
A. 2017
B. 2011
C. 2015
D. 2019
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42. What Is The Purpose Of Ibm Watson ?
A. Computer Hardware
B. Making Games
C. Chatbot
D. Question Answer System
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43. On Which Platform Alexa Assistant Is Working ?
A. Pixabay
B. Amazon
C. Google
D. Yahoo
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44. Why We Need Ai Those Days ?
A. Massive Amount Of Data
B. To Develop Machines
C. Decrease Population
D. Increase Population
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45. Which Algorithm Is Example Of Reinforcement Learning ?
A. Supervised Learning
B. Q-Learning
C. Unsupervised Learning
D. Semi Supervised Learning
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46. Unsupervised Learning Solves Which Type Of Problems ?
A. Clustering
B. Regression
C. Classification
D. None Of Them
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47. Supervised Learning Solves Which Type Of Problems ?
A. Clustering
B. Regression
C. Classification
D. None Of Them
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48. Reinforcement Learning Solve Which Type Of Problems ?
A. Clustering
B.Reward Based
C. Regression
D. Classification
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49. In Reinforcement Learning Type Of Data Is.
A. Labeled Data
B. Unlabeled Data
C. No Pre-Defined Data
D. Both A & B
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50. In Supervised Learning Training Is Under.
A. External Supervision
B. Internal Supervision
C. No Supervision
D. None Of Them
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51. In Unsupervised Learning Training Is Under.
A. External Supervision
B. Internal Supervision
C. No Supervision
D. None Of Them
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52. In Reinforcement Learning Training Is Under.
A. External Supervision
B. Internal Supervision
C. No Supervision
D. None Of Them
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53. In Supervised Learning Output Is.
A. Known
B. Unknown
C. Both A & B
D. None Of Them
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54. In Unsupervised Learning Output Is.
A. Known
B. Unknown
C. Both A & B
D. Understand Patterns And Discover Output
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55. In Reinforcement Learning Output Is.
A. Understand Patterns And Discover Output
B. Known
C. Follow Trail And Error Method
D. Unknown
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56. What Is Example Of Regression ?
A. Predict Stock Market Price
B. Spam And Non-Spam Emails
C. Transactions That Are Fraud In Nature
D. None Of Them
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57. What Is Example Of Classification ?
A. Predict Stock Market Price
B. Spam And Non-Spam Emails
C. Transactions That Are Fraud In Nature
D. None Of Them
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58. What Is Example Of Clustering ?
A. Predict Stock Market Price
B. Spam And Non-Spam Emails
C. Transactions That Are Fraud In Nature
D. None Of Them
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59. Which Is Regression Algorithm.
A. Linear Regression
B. Logistic Regression
C. Both A & B
D. None Of Them
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60. Which Is Classification Algorithm.
A. Linear Regression
B. Logistic Regression
C. Both A & B
D. None Of Them
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61. Output Of Regression Model Is.
A. Categorical Quantity
B.Continuous Quantity
C. Both A & B
D. None Of Them
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62. Output Of Classification Model Is.
A. Categorical Quantity
B.Continuous Quantity
C. Both A & B
D. None Of Them
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63. Decision Tree Is Which Type Of Machine Learning Algorithm.
A. Supervised Learning
B. Q-Learning
C. Unsupervised Learning
D. Semi Supervised Learning
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64. In Decision Tree Root Node Represent.
A. Input
B. Output
C. Predictor Variable
D. None Of Them
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65. In Decision Tree Each Leaf Node Represent.
A. Input
B. Output
C. Predictor Variable
D. None Of Them
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66. Multiple Decision Tree Combine To Make A.
A. K-Means
B. Cnn
C. Random Forest
D. None Of Them
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67. If You Want To Avoid Over-Fitting You Use.
A. K-Means
B. Random Forest
C. Cnn
D. None Of Them
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68. The Sample Dataset That Does Not Include In Bootstrapped Dataset Is Called.
A. Bag Of Words
B. Tfidf
C. Out-Of-Bag (Oob)Dataset
D. None Of Them
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69. In Real World, How Much Data Is Not Included In Bootstrap Dataset ?
A. 1/3rd
B. 2/3rd
C. 0/3rd
D. None Of Them
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70. Naive Bayes Solve Which Type Of Problems.
A. Classification
B. Regression
C. Both A & B
D. None Of Them
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71. The Approach That Is Used By Naive Bayes To Solve A Problem.
A. Realistic Approach
B. Probabilistic Approach
C. Both A & B
D. None Of Them
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72. Which Variable Or Which Feature Best Splits The Data.
A. Information Gain
B. Entropy
C. Both A & B
D. None Of Them
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73. Why Random Forest ?
A. More Accuracy
B. Avoid Over-Fitting
C. Bagging
D. All Of Them
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74. Which Algorithm Is Used To Classify Data Into Different Classes ?
A. Random Forest
B. Knn
C. Svm
D. Linear Regression
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75. Box-Plot Is Mainly Used In ?
A. Data Distribution
B. Data Gathering
C. Exploratory Data Analysis
D. None Of Them
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76. Which Concept Deep Learning Used To Solve Complex Problems.
A. Svm
B. Neural Networks
C. Knn
D. Cnn
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77. Limitation Of Machine Learning is.
A. To Handle High Dimensional Data
B. To Give Accurate Output
C. To Handle Low Dimensional Data
D. None Of Them
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78. Deep Learning Is One Of The Only Method By Which We Can Overcome The Challenges Of.
A. Prediction
B. Feature Extraction
C. Training Model
D. None Of Them
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79. The First Layer Of Deep Learning Is Known As.
A. Input Layer
B. Output Layer
C. Hidden Layer
D. None Of Them
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80. A Single Layer Perceptron is.
A. Linear Classifier
B. Binary Classifier
C. Both A & B
D. None Of Them
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81. Multilayer Perceptron Contain One Or More Hidden Layer That’s Why It Considers.
A. Neural Network
B. Deep Neural Network
C. Svm
D. None Of Them
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82. A Very Important Concept Of The Multiple Layer Perceptron Is.
A. Feature Extraction
B. Data Processing
C. Back Propagation
D. None Of Them
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83. Training A Neural Network Is All About.
A. Inputs
B. Back Propagation
C. Desired Outputs
D. None Of Them
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84. Which Method Is Used To Reduced The Error / Loss In The Network.
A. Gradient Descent
B. Gbm
C. Svm
D. None Of Them
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85. For Scaling Which Method Is Used.
A. Scaling
B. Minmaxscaler
C. Measuring
D. None Of Them
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86. Breaking A Complex Sentences Into Words Is Called.
A. Stemming
B. Lemmatization
C. Tokenization
D. None Of Them
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87. Normalizing Words Into Its Base Form Is Known As.
A. Stemming
B. Lemmatization
C. Tokenization
D. None Of Them
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88. The Morphological Analysis Of Words Is Done By.
A. Stemming
B. Lemmatization
C. Tokenization
D. None Of Them
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89. The Intelligence Displayed By Humans And Other Animals Is Termed.
A. Constance
B. Ability
C. Natural Intelligence
D. Cognition
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90. An Evolved Definition Of Artificial Intelligence Led To A Phenomenon Known As The
A. Formulation
B. Data Processing
C. Ai Effect
D. Machination
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91. The Nodes That Have No Child Is Called____?
A. Dead Node
B. Root Node
C. Both Of Them
D. None Of These
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92. If A Machine Answers Ambiguous Questions, Then It Is Called.
A. Machine
B. Intelligent Machine
C. Local Machine
D. Fast Machine
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93. A Systematic Approach H To Solve A Problem Is Called .
A. Problem Space
B. Line Space
C. Tree Space
D. None Of These
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94. The Graphical Representation Of Solution Space Can Also Be Done With___?
A. Node
B. Tree
C. Table
D. None Of These
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95. The Node Which Has No Parent Is Called___.
A. Leaf Node
B. Decision Node
C. Both A And B
D. Root Node
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96. After Finding All The Child Of A Node, Then A Node Is Said To Be ?
A. Open Node
B. Closed Node
C. Child Node
D. Middle Node
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97. A Node That Has One Or More Link Between Parent And Itself Is Called____.
A. Decendant
B. Ancestor
C. Root
D. None Of These
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98. Blind Search Is Also Known As.
A. Informed Search
B. Heuristic Search
C. Uninformed Search
D. Simple Search
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99. Number Of Nodes Expending From A Node To Calculate An Average Is Called.
A. Height Of Tree
B. Depth Of Tree
C. Level Of Tree
D. Branching Factor
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100. The Lowest Leaf Of A Tree.
A. Height Of A Tree
B. Length Of A Tree
C. Level Of A Tree
D. None Of A Tree
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101. Category Of Information That Control A Search .
A. Dfs
B. Bfs
C. Linear Search
D. Heuristic Search
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102. The Search That Stops Instantly After Finding The Solution.
A. Optimal Search
B. Non-Optimal Search
C. Informed Search
D. Depth First Search
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103. The Major Problem With Breath First Search Is.
A. Space
B. Time
C. Resources
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104. Deeping Progression Emulates Two Techniques.
A. Dfs & Beam Search
B. Bfs & Beam Search
C. Dfs & Bfs
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105. Brute Force Search Is Used When We Have___.
A. Finite Node
B. Infinite Node
C. Primary Node
D. None Of These
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