MCQOPTIONS
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MCQOPTIONS
This section includes 210 Mcqs, each offering curated multiple-choice questions to sharpen your Artificial Intelligence knowledge and support exam preparation. Choose a topic below to get started.
| 51. |
Which variable can give the concrete form to the representation of the transition model? |
| A. | Single variable |
| B. | Discrete state variable |
| C. | Random variable |
| D. | Both Single & Discrete state variable |
| Answer» E. | |
| 52. |
____________ is/are the way/s to represent uncertainty. |
| A. | Fuzzy Logic |
| B. | Probability |
| C. | Entropy |
| D. | All of the mentioned |
| Answer» E. | |
| 53. |
Fuzzy logic is usually represented as |
| A. | IF-THEN-ELSE rules |
| B. | IF-THEN rules |
| C. | Both IF-THEN-ELSE rules & IF-THEN rules |
| D. | None of the mentioned |
| Answer» C. Both IF-THEN-ELSE rules & IF-THEN rules | |
| 54. |
There are also other operators, more linguistic in nature, called __________ that can be applied to fuzzy set theory. |
| A. | Hedges |
| B. | Lingual Variable |
| C. | Fuzz Variable |
| D. | None of the mentioned |
| Answer» B. Lingual Variable | |
| 55. |
Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the following. |
| A. | AND |
| B. | OR |
| C. | NOT |
| D. | All of the mentioned |
| Answer» E. | |
| 56. |
The room temperature is hot. Here the hot (use of linguistic variable is used) can be represented by ____ |
| A. | Fuzzy Set |
| B. | Crisp Set |
| C. | Fuzzy & Crisp Set |
| D. | None of the mentioned |
| Answer» B. Crisp Set | |
| 57. |
The truth values of traditional set theory is ____________ and that of fuzzy set is ________ |
| A. | Either 0 or 1, between 0 & 1 |
| B. | Between 0 & 1, either 0 or 1 |
| C. | Between 0 & 1, between 0 & 1 |
| D. | Either 0 or 1, either 0 or 1 |
| Answer» B. Between 0 & 1, either 0 or 1 | |
| 58. |
What is the consequence between a node and its predecessors while creating bayesian network? |
| A. | Functionally dependent |
| B. | Dependant |
| C. | Conditionally independent |
| D. | Both Conditionally dependant & Dependant |
| Answer» D. Both Conditionally dependant & Dependant | |
| 59. |
Which condition is used to influence a variable directly by all the others? |
| A. | Partially connected |
| B. | Fully connected |
| C. | Local connected |
| D. | None of the mentioned |
| Answer» C. Local connected | |
| 60. |
What is meant by probability density function? |
| A. | Probability distributions |
| B. | Continuous variable |
| C. | Discrete variable |
| D. | Probability distributions for Continuous variables |
| Answer» E. | |
| 61. |
Which variable cannot be written in entire distribution as a table? |
| A. | Discrete |
| B. | Continuous |
| C. | Both Discrete & Continuous |
| D. | None of the mentioned |
| Answer» C. Both Discrete & Continuous | |
| 62. |
How the distance between two shapes can be defined? |
| A. | Weighted sum of the shape |
| B. | Size of the shape |
| C. | Shape context |
| D. | None of the mentioned |
| Answer» B. Size of the shape | |
| 63. |
Which describes the coarse arrangement of the rest of the shape with respect to the point? |
| A. | Shape |
| B. | Context |
| C. | Shape context |
| D. | None of the mentioned |
| Answer» D. None of the mentioned | |
| 64. |
What kind of interpretation is done by adding context-dependant information? |
| A. | Semantic |
| B. | Syntactic |
| C. | Pragmatic |
| D. | None of the mentioned |
| Answer» D. None of the mentioned | |
| 65. |
How many types of quantification are available in artificial intelligence? |
| A. | 1 |
| B. | 2 |
| C. | 3 |
| D. | 4 |
| Answer» C. 3 | |
| 66. |
What can’t be done in the semantic interpretation? |
| A. | Logical term |
| B. | Complete logical sentence |
| C. | Both Logical term & Complete logical sentence |
| D. | None of the mentioned |
| Answer» D. None of the mentioned | |
| 67. |
Incorrect information results in unsatisfied preconditions for actions and plans _____________ detects violations of the preconditions for successful completion of the plan. |
| A. | Conditional Plan |
| B. | Conformant Planning |
| C. | Execution monitoring |
| D. | Both Conditional Plan & Execution monitoring |
| Answer» D. Both Conditional Plan & Execution monitoring | |
| 68. |
Standard planning algorithms assumes environment to be |
| A. | Deterministic |
| B. | Fully observable |
| C. | Single agent |
| D. | Stochastic |
| Answer» B. Fully observable | |
| 69. |
__________ planning allows the agent to take advice from the domain designer in the form of decomposition rules. |
| A. | GraphPlan |
| B. | Hierarchical task network (HTN) |
| C. | SatPlan |
| D. | None of the mentioned |
| Answer» C. SatPlan | |
| 70. |
_________ algorithm translates a planning problem in to prepositional axioms. |
| A. | GraphPlan |
| B. | SatPlan |
| C. | Greedy |
| D. | None of the mentioned |
| Answer» C. Greedy | |
| 71. |
Planning problem combines the two major aspects of AI |
| A. | Search & Logic |
| B. | Logic & Knowledge Based Systems |
| C. | FOL & Logic |
| D. | Knowledge Based Systems |
| Answer» B. Logic & Knowledge Based Systems | |
| 72. |
What is the other name of each plan resulted in partial order planning? |
| A. | Polarization |
| B. | Linearization |
| C. | Solarization |
| D. | None of the mentioned |
| Answer» C. Solarization | |
| 73. |
____________ algorithms is used to extract the plan directly from the planning graph, rather than using graph to provide heuristic. |
| A. | BFS/DFS |
| B. | A* |
| C. | Graph-Plan |
| D. | Greedy |
| Answer» D. Greedy | |
| 74. |
Planning graphs consists of |
| A. | a sequence of levels |
| B. | a sequence of levels which corresponds to time steps in the plan |
| C. | a sequence of actions which corresponds to the state of the system |
| D. | none of the mentioned |
| Answer» C. a sequence of actions which corresponds to the state of the system | |
| 75. |
To eliminate the inaccuracy problem in planning problem or partial order planning problem we can use ___________________ data structure/s. |
| A. | Stacks |
| B. | Queue |
| C. | BST (Binary Search Tree) |
| D. | Planning Graphs |
| Answer» E. | |
| 76. |
The famous spare tire problem or Scheduling classes for bunch of students or Air cargo transport are the best example of |
| A. | Planning problem |
| B. | Partial Order planning problem |
| C. | Total order planning |
| D. | None of the mentioned |
| Answer» B. Partial Order planning problem | |
| 77. |
The process by which the brain orders actions needed to complete a specific task is referred as, |
| A. | Planning problem |
| B. | Planning problem |
| C. | Total order planning |
| D. | Both Planning problem & Partial order planning |
| Answer» E. | |
| 78. |
What is called inconsistent support? |
| A. | If two literals are not negation of other |
| B. | If two literals are negation of other |
| C. | Mutually exclusive |
| D. | None of the mentioned |
| Answer» C. Mutually exclusive | |
| 79. |
How many conditions are available between two actions in mutex relation? |
| A. | 1 |
| B. | 2 |
| C. | 3 |
| D. | 4 |
| Answer» D. 4 | |
| 80. |
Which can be adapted for planning algorithm? |
| A. | Most-constrained variable |
| B. | Most-constrained literal |
| C. | constrained |
| D. | None of the mentioned |
| Answer» B. Most-constrained literal | |
| 81. |
What are not present in finish actions? |
| A. | Preconditions |
| B. | Effect |
| C. | Finish |
| D. | None of the mentioned |
| Answer» C. Finish | |
| 82. |
What are not present in start actions? |
| A. | Preconditions |
| B. | Effect |
| C. | Finish |
| D. | None of the mentioned |
| Answer» B. Effect | |
| 83. |
Uncertainty arises in the Wumpus world because the agent’s sensors give only |
| A. | Full & Global information |
| B. | Partial & Global Information |
| C. | Partial & local Information |
| D. | Full & local information |
| Answer» D. Full & local information | |
| 84. |
A constructive approach in which no commitment is made unless it is necessary to do so, is |
| A. | Least commitment approach |
| B. | Most commitment approach |
| C. | Nonlinear planning |
| D. | Opportunistic planning |
| Answer» B. Most commitment approach | |
| 85. |
A plan that describe how to take actions in levels of increasing refinement and specificity is |
| A. | Problem solving |
| B. | Planning |
| C. | Non-hierarchical plan |
| D. | Hierarchical plan |
| Answer» E. | |
| 86. |
What are you predicating by the logic: ۷x: €y: loyalto(x, y). |
| A. | Everyone is loyal to someone |
| B. | Everyone is loyal to all |
| C. | Everyone is not loyal to someone |
| D. | Everyone is loyal |
| Answer» B. Everyone is loyal to all | |
| 87. |
In partial order plan. A. Relationships between the actions of the behavior are set prior to the actions B. Relationships between the actions of the behavior are not set until absolutely necessary Choose the correct option. |
| A. | A is true |
| B. | B is true |
| C. | Either A or B can be true depending upon situation |
| D. | Neither A nor B is true |
| Answer» B. B is true | |
| 88. |
How the buckets are stored in predicate indexing? |
| A. | Lists |
| B. | Stack |
| C. | Hashes |
| D. | None of the mentioned |
| Answer» D. None of the mentioned | |
| 89. |
What is meant by predicate indexing? |
| A. | All the one kind of facts in one bucket and another kind in other bucket |
| B. | Acts like index for facts |
| C. | All of the mentioned |
| D. | None of the mentioned |
| Answer» B. Acts like index for facts | |
| 90. |
Antonymy relation means, |
| A. | A is part of B |
| B. | B has A as a part of itself |
| C. | A denotes opposite of B |
| D. | A is superordinate of B |
| Answer» D. A is superordinate of B | |
| 91. |
Synonymy relation means, |
| A. | A is part of B |
| B. | A denotes same as B |
| C. | A is a kind of B |
| D. | A is superordinate of B |
| Answer» C. A is a kind of B | |
| 92. |
Following is an extension of the semantic network. |
| A. | Expert Systems |
| B. | Rule Based Expert Systems |
| C. | Decision Tree Based networks |
| D. | Partitioned Networks |
| Answer» E. | |
| 93. |
Holonymy relation means, |
| A. | A is part of B |
| B. | B has A as a part of itself |
| C. | A is a kind of B |
| D. | A is superordinate of B |
| Answer» C. A is a kind of B | |
| 94. |
________ is/are the well known Expert System/s for medical diagnosis systems |
| A. | MYSIN |
| B. | CADUCEUS |
| C. | DENDRAL |
| D. | SMH.PAL |
| Answer» B. CADUCEUS | |
| 95. |
Autonomous Question/Answering systems are |
| A. | Expert Systems |
| B. | Rule Based Expert Systems |
| C. | Decision Tree Based Systems |
| D. | All of the mentioned |
| Answer» E. | |
| 96. |
Forward chaining systems are _____________ where as backward chaining systems are ________ |
| A. | Goal-driven, goal-driven |
| B. | Goal-driven, data-driven |
| C. | Data-driven, goal-driven |
| D. | Data-driven, data-driven |
| Answer» D. Data-driven, data-driven | |
| 97. |
Translate the following statement into FOL. “For every a, if a is a PhD student, then a has a master degree” |
| A. | ∀ a PhD(a) -> Master(a) |
| B. | ∃ a PhD(a) -> Master(a) |
| C. | A is true, B is true |
| D. | A is false, B is false |
| Answer» B. ∃ a PhD(a) -> Master(a) | |
| 98. |
What among the following could the Existential instantiation of ∃x Crown(x) ^ OnHead(x, Johnny) |
| A. | Crown(John) ^ OnHead(John, Jonny) |
| B. | Crown(y) ^ OnHead(y, Jonny) |
| C. | Crown(x) ^ OnHead(x, Jonny) |
| D. | None of the mentioned |
| Answer» C. Crown(x) ^ OnHead(x, Jonny) | |
| 99. |
Lifted inference rules require finding substitutions that make different logical expressions looks identical. |
| A. | Existential Instantiation |
| B. | Universal Instantiation |
| C. | Unification |
| D. | Modus Ponen |
| Answer» D. Modus Ponen | |
| 100. |
Which of the following is not the style of inference? |
| A. | Forward Chaining |
| B. | Backward Chaining |
| C. | Resolution Refutation |
| D. | Modus Ponen |
| Answer» E. | |