Multiple Choice
Questions and Answers:-
1. A 3-input neuron is
trained to output a zero when the input is 110 and a one when the input is 111.
After generalization, the output will be zero when and only when the input is:
a) 000 or 110 or 011 or 101
b) 010 or 100 or 110 or 101
c) 000 or 010 or 110 or 100
d) 100 or 111 or 101 or 001
Answer: c
Explanation: The truth table before
generalization is:
Inputs Output
000 $
001 $
010 $
011 $
100 $
101 $
110 0
111 1
where $ represents don’t know cases and the
output is random.
After generalization, the truth table becomes:
Inputs Output
000 0
001 1
010 0
011 1
100 0
101 1
110 0
111 1
.
2. A perceptron is:
a) a single layer feed-forward neural network
with pre-processing
b) an auto-associative neural network
c) a double layer auto-associative neural
network
d) a neural network that contains feedback
Answer: a
Explanation: The perceptron is a single layer
feed-forward neural network. It is not an auto-associative network because it
has no feedback and is not a multiple layer neural network because the
pre-processing stage is not made of neurons.
3. An auto-associative
network is:
a) a neural network that contains no loops
b) a neural network that contains feedback
c) a neural network that has only one loop
d) a single layer feed-forward neural network
with pre-processing
Answer: b
Explanation: An auto-associative network is
equivalent to a neural network that contains feedback. The number of feedback
paths(loops) does not have to be one.
4. A 4-input neuron has
weights 1, 2, 3 and 4. The transfer function is linear with the constant of
proportionality being equal to 2. The inputs are 4, 10, 5 and 20 respectively.
The output will be:
a) 238
b) 76
c) 119
d) 123
Answer: a
Explanation: The output is found by
multiplying the weights with their respective inputs, summing the results and
multiplying with the transfer function. Therefore:
Output = 2 * (1*4 + 2*10 + 3*5 + 4*20) = 238.
5. Which of the
following is true?
(i) On average, neural networks have higher
computational rates than conventional computers.
(ii) Neural networks learn by example.
(iii) Neural networks mimic the way the human
brain works.
a) All of the mentioned are true
b) (ii) and (iii) are true
c) (i), (ii) and (iii) are true
d) None of the mentioned
Answer: a
Explanation: Neural networks have higher
computational rates than conventional computers because a lot of the operation
is done in parallel. That is not the case when the neural network is simulated
on a computer. The idea behind neural nets is based on the way the human brain
works. Neural nets cannot be programmed, they cam only learn by examples.
6. Which of the
following is true for neural networks?
(i) The training time depends on the size of
the network.
(ii) Neural networks can be simulated on a
conventional computer.
(iii) Artificial neurons are identical in
operation to biological ones.
a) All of the mentioned
b) (ii) is true
c) (i) and (ii) are true
d) None of the mentioned
Answer: c
Explanation: The training time depends on the
size of the network; the number of neuron is greater and therefore the number
of possible ‘states’ is increased. Neural networks can be simulated on a
conventional computer but the main advantage of neural networks – parallel
execution – is lost. Artificial neurons are not identical in operation to the
biological ones.
7. What are the
advantages of neural networks over conventional computers?
(i) They have the ability to learn by example
(ii) They are more fault tolerant
(iii)They are more suited for real time
operation due to their high ‘computational’ rates
a) (i) and (ii) are true
b) (i) and (iii) are true
c) Only (i)
d) All of the mentioned
Answer: d
Explanation: Neural networks learn by example.
They are more fault tolerant because they are always able to respond and small
changes in input do not normally cause a change in output. Because of their
parallel architecture, high computational rates are achieved.
8. Which of the
following is true?
Single layer associative neural networks do
not have the ability to:
(i) perform pattern recognition
(ii) find the parity of a picture
(iii)determine whether two or more shapes in a
picture are connected or not
a) (ii) and (iii) are true
b) (ii) is true
c) All of the mentioned
d) None of the mentioned
Answer: a
Explanation: Pattern recognition is what
single layer neural networks are best at but they don’t have the ability to
find the parity of a picture or to determine whether two shapes are connected
or not.
9. Which is true for
neural networks?
a) It has set of nodes and connections
b) Each node computes it’s weighted input
c) Node could be in excited state or
non-excited state
d) All of the mentioned
Answer: d
Explanation: All mentioned are the
characteristics of neural network.
10. Neuro software is:
a) A software used to analyze neurons
b) It is powerful and easy neural network
c) Designed to aid experts in real world
d) It is software used by Neuro surgeon
Answer: b
11. Why is the XOR
problem exceptionally interesting to neural network researchers?
a) Because it can be expressed in a way that
allows you to use a neural network
b) Because it is complex binary operation that
cannot be solved using neural networks
c) Because it can be solved by a single layer
perceptron
d) Because it is the simplest linearly
inseparable problem that exists.
Answer: d
12. What is back
propagation?
a) It is another name given to the curvy
function in the perceptron
b) It is the transmission of error back
through the network to adjust the inputs
c) It is the transmission of error back
through the network to allow weights to be adjusted so that the network can
learn.
d) None of the mentioned
Answer: c
Explanation: Back propagation is the
transmission of error back through the network to allow weights to be adjusted
so that the network can learn.
13. Why are linearly
separable problems of interest of neural network researchers?
a) Because they are the only class of problem
that network can solve successfully
b) Because they are the only class of problem
that Perceptron can solve successfully
c) Because they are the only mathematical
functions that are continue
d) Because they are the only mathematical
functions you can draw
Answer: b
Explanation: Linearly separable problems of
interest of neural network researchers because they are the only class of
problem that Perceptron can solve successfully
14. Which of the
following is not the promise of artificial neural network?
a) It can explain result
b) It can survive the failure of some nodes
c) It has inherent parallelism
d) It can handle noise
Answer: a
Explanation: The artificial Neural Network
(ANN) cannot explain result.
15. Neural Networks are
complex ______________ with many parameters.
a) Linear Functions
b) Nonlinear Functions
c) Discrete Functions
d) Exponential Functions
Answer: a
Explanation: Neural networks are complex
linear functions with many parameters.
16. A perceptron adds up
all the weighted inputs it receives, and if it exceeds a certain value, it
outputs a 1, otherwise it just outputs a 0.
a) True
b) False
c) Sometimes – it can also output intermediate
values as well
d) Can’t say
Answer: a
Explanation: Yes the perceptron works like
that.
17. The name for the
function in question 16 is
a) Step function
b) Heaviside function
c) Logistic function
d) Perceptron function
Answer: b
Explanation: Also known as the step function –
so answer 1 is also right. It is a hard thresholding function, either on or off
with no in-between.
18. Having multiple
perceptrons can actually solve the XOR problem satisfactorily: this is because
each perceptron can partition off a linear part of the space itself, and they
can then combine their results.
a) True – this works always, and these multiple
perceptrons learn to classify even complex problems.
b) False – perceptrons are mathematically
incapable of solving linearly inseparable functions, no matter what you do
c) True – perceptrons can do this but are
unable to learn to do it – they have to be explicitly hand-coded
d) False – just having a single perceptron is
enough
Answer: c
19. The network that
involves backward links from output to the input and hidden layers is called as
____.
a) Self organizing maps
b) Perceptrons
c) Recurrent neural network
d) Multi layered perceptron
Answer: c
Explanation: RNN (Recurrent neural network)
topology involves backward links from output to the input and hidden layers.
20. Which of the
following is an application of NN (Neural Network)?
a) Sales forecasting
b) Data validation
c) Risk management
d) All of the mentioned
Answer: d
Explanation: All mentioned options are
applications of Neural Network.
21. Different learning
method does not include:
a) Memorization
b) Analogy
c) Deduction
d) Introduction
Answer: d
Explanation: Different learning methods
include memorization, analogy and deduction.
22. Following are the
advantage/s of Decision Trees. Choose that apply.
a) Possible Scenarios can be added
b) For data including categorical variables
with different number of levels, information gain in decision trees are biased
in favor of those attributes with more levels
c) Worst, best and expected values can be
determined for different scenarios
d) Use a white box model, If given result is
provided by a model
Answer: a, c, d
23. Which of the
following is the model used for learning?
a) Decision trees
b) Neural networks
c) Propositional and FOL rules
d) All of the mentioned
Answer: d
Explanation: Decision tress, Neural networks,
Propositional rules and FOL rules all are the models of learning.
24. Automated vehicle is
an example of ______.
a) Supervised learning
b) Unsupervised learning
c) Active learning
d) Reinforcement learning
Answer: a
Explanation: In automatic vehicle set of
vision inputs and corresponding actions are available to learner hence it’s an
example of supervised learning.
25. Following is an
example of active learning:
a) News recommendation system
b) Dust cleaning machine
c) Automated vehicle
d) None of the mentioned
Answer: a
Explanation: In active learning, not only the
teacher is available but the learner can ask suitable perception-action pair
example to improve performance.
26. In which of the
following learning the teacher returns reward and punishment to learner?
a) Active learning
b) Reinforcement learning
c) Supervised learning
d) Unsupervised learning
Answer: b
Explanation: Reinforcement learning is the
type of learning in which teacher returns award or punishment to learner.
27. Decision trees are
appropriate for the problems where:
a) Attributes are both numeric and nominal
b) Target function takes on a discrete number
of values.
c) Data may have errors
d) All of the mentioned
Answer: d
Explanation: Decision trees can be used in all
the conditions stated.
28. Which of the
following is not an application of learning?
a) Data mining
b) WWW
c) Speech recognition
d) None of the mentioned
Answer: d
Explanation: All mentioned options are
applications of learning.
29. Which of the
following is the component of learning system?
a) Goal
b) Model
c) Learning rules
d) All of the mentioned
Answer: d
Explanation: Goal, model, learning rules and
experience are the components of learning system.
30. Following is also
called as exploratory learning:
a) Supervised learning
b) Active learning
c) Unsupervised learning
d) Reinforcement learning
Answer: c
Explanation: In unsupervised learning no teacher
is available hence it is also called unsupervised learning.
31. A _________ is a
decision support tool that uses a tree-like graph or model of decisions and
their possible consequences, including chance event outcomes, resource costs,
and utility.
a) Decision tree
b) Graphs
c) Trees
d) Neural Networks
Answer: a
Explanation: Refer the definition of Decision
tree.
32. Decision Tree is a
display of an algorithm.
a) True
b) False
Answer: a
33. Decision Tree is
a) Flow-Chart
b) Structure in which internal node represents
test on an attribute, each branch represents outcome of test and each leaf node
represents class label
c) Both a) & b)
d) None of the mentioned
Answer: c
Explanation: Refer the definition of Decision
tree.
34. Decision Trees can
be used for Classification Tasks.
a) True
b) False
Answer: a
35. How many types of
learning are available in machine learning?
a) 1
b) 2
c) 3
d) 4
Answer: c
Explanation: The three types of machine
learning are supervised, unsupervised and reinforcement.
36. Choose from the
following that are Decision Tree nodes
a) Decision Nodes
b) Weighted Nodes
c) Chance Nodes
d) End Nodes
Answer: a, c, d
37. Decision Nodes are
represented by,
a) Disks
b) Squares
c) Circles
d) Triangles
Answer: b
38. Chance Nodes are
represented by,
a) Disks
b) Squares
c) Circles
d) Triangles
Answer: c
39. End Nodes are
represented by,
a) Disks
b) Squares
c) Circles
d) Triangles
Answer: d
40. How the decision
tree reaches its decision?
a) Single test
b) Two test
c) Sequence of test
d) No test
Answer: c
Explanation: A decision tree reaches its
decision by performing a sequence of tests.
41. What will take place
as the agent observes its interactions with the world?
a) Learning
b) Hearing
c) Perceiving
d) Speech
Answer:a
Explanation:Learning will take place as the
agent observes its interactions with the world and its own decision making
process.
42. Which modifies the
performance element so that it makes better decision?
a) Performance element
b) Changing element
c) Learning element
d) None of the mentioned
Answer:c
Explanation:A learning element modifies the
performance element so that it can make better decision.
43. How many things are
concerned in design of a learning element?
a) 1
b) 2
c) 3
d) 4
Answer:c
Explanation:The three main issues are affected
in design of a learning element are components, feedback and representation.
44. What is used in
determining the nature of the learning problem?
a) Environment
b) Feedback
c) Problem
d) All of the mentioned
Answer:b
Explanation:The type of feedback is used in
determining the nature of the learning problem that the agent faces.
45. How many types are
available in machine learning?
a) 1
b) 2
c) 3
d) 4
Answer:c
Explanation:The three types of machine
learning are supervised, unsupervised and reinforcement.
46. Which is used for
utility functions in game playing algorithm?
a) Linear polynomial
b) Weighted polynomial
c) Polynomial
d) Linear weighted polynomial
Answer:d
Explanation:Linear weighted polynomial is used
for learning element in the game playing programs.
47. Which is used to
choose among multiple consistent hypotheses?
a) Razor
b) Ockham razor
c) Learning element
d) None of the mentioned
Answer:b
Explanation:Ockham razor prefers the simplest
hypothesis consistent with the data intuitively.
48. What will happen if
the hypothesis space contains the true function?
a) Relizable
b) Unrelizable
c) Both a & b
d) None of the mentioned
Answer:b
Explanation:A learning problem is realizable
if the hypothesis space contains the true function.
49. What takes input as
an object described bya set of attributes?
a) Tree
b) Graph
c) Decision graph
d) Decision tree
Answer:d
Explanation:Decision tree takes input as an
object described by a set of attributes and returns a decision.
50. How the decision
tree reaches its decision?
a) Single test
b) Two test
c) Sequence of test
d) No test
Answer:c
Explanation:A decision tree reaches its
decision by performing a sequence of tests.
51. What will take place
as the agent observes its interactions with the world?
a) Learning
b) Hearing
c) Perceiving
d) Speech
Answer: a
Explanation: Learning will take place as the
agent observes its interactions with the world and its own decision making
process.
52. Which modifies the
performance element so that it makes better decision?
a) Performance element
b) Changing element
c) Learning element
d) None of the mentioned
Answer: c
Explanation: A learning element modifies the
performance element so that it can make better decision.
53. How many things are
concerned in design of a learning element?
a) 1
b) 2
c) 3
d) 4
Answer: c
Explanation: The three main issues are
affected in design of a learning element are components, feedback and
representation.
54. What is used in
determining the nature of the learning problem?
a) Environment
b) Feedback
c) Problem
d) All of the mentioned
Answer: b
Explanation: The type of feedback is used in
determining the nature of the learning problem that the agent faces.
55. How many types are
available in machine learning?
a) 1
b) 2
c) 3
d) 4
Answer: c
Explanation: The three types of machine
learning are supervised, unsupervised and reinforcement.
56. Which is used for
utility functions in game playing algorithm?
a) Linear polynomial
b) Weighted polynomial
c) Polynomial
d) Linear weighted polynomial
Answer: d
Explanation: Linear weighted polynomial is
used for learning element in the game playing programs.
57. Which is used to
choose among multiple consistent hypotheses?
a) Razor
b) Ockham razor
c) Learning element
d) None of the mentioned
Answer: b
Explanation: Ockham razor prefers the simplest
hypothesis consistent with the data intuitively.
58. What will happen if
the hypothesis space contains the true function?
a) Realizable
b) Unrealizable
c) Both a & b
d) None of the mentioned
Answer: b
Explanation: A learning problem is realizable
if the hypothesis space contains the true function.
59. What takes input as
an object described by a set of attributes?
a) Tree
b) Graph
c) Decision graph
d) Decision tree
Answer: d
Explanation: Decision tree takes input as an
object described by a set of attributes and returns a decision.
60. How the decision
tree reaches its decision?
a) Single test
b) Two test
c) Sequence of test
d) No test
Answer: c
Explanation: A decision tree reaches its
decision by performing a sequence of tests.
61. Factors which affect
the performance of learner system does not include
a) Representation scheme used
b) Training scenario
c) Type of feedback
d) Good data structures
Answer: d
Explanation: Factors which affect the
performance of learner system does not include good data structures.
62. Different learning
method does not include:
a) Memorization
b) Analogy
c) Deduction
d) Introduction
Answer: d
Explanation: Different learning methods
include memorization, analogy and deduction.
63. Which of the
following is the model used for learning?
a) Decision trees
b) Neural networks
c) Propositional and FOL rules
d) All of the mentioned
Answer: d
Explanation: Decision trees, Neural networks,
Propositional rules and FOL rules all are the models of learning.
64. Automated vehicle is
an example of ______.
a) Supervised learning
b) Unsupervised learning
c) Active learning
d) Reinforcement learning
Answer: a
Explanation: In automatic vehicle set of
vision inputs and corresponding actions are available to learner hence it’s an
example of supervised learning.
65. Following is an
example of active learning:
a) News Recommender system
b) Dust cleaning machine
c) Automated vehicle
d) None of the mentioned
Answer: a
Explanation: In active learning, not only the
teacher is available but the learner can ask suitable perception-action pair
example to improve performance.
66. In which of the following
learning the teacher returns reward and punishment to learner?
a) Active learning
b) Reinforcement learning
c) Supervised learning
d) Unsupervised learning
Answer: b
Explanation: Reinforcement learning is the
type of learning in which teacher returns award or punishment to learner.
67. Decision trees are
appropriate for the problems where:
a) Attributes are both numeric and nominal
b) Target function takes on a discrete number
of values.
c) Data may have errors
d) All of the mentioned
Answer: d
Explanation: Decision trees can be used in all
the conditions stated.
68. Which of the
following is not an application of learning?
a) Data mining
b) WWW
c) Speech recognition
d) None of the mentioned
Answer: d
Explanation: All mentioned options are
applications of learning.
69. Which of the
following is the component of learning system?
a) Goal
b) Model
c) Learning rules
d) All of the mentioned
Answer: d
Explanation: Goal, model, learning rules and
experience are the components of learning system.
70. Following is also
called as exploratory learning:
a) Supervised learning
b) Active learning
c) Unsupervised learning
d) Reinforcement learning
Answer: c
Explanation: In unsupervised learning no
teacher is available hence it is also called unsupervised learning.
71. Which is not a
desirable property of a logical rule-based system?
a) Locality
b) Attachment
c) Detachment
d) Truth-Functionality
e) Global attribute
Answer: b
Explanation: Locality: In logical systems,
whenever we have a rule of the form A => B, we can conclude B, given
evidence A, without worrying about any other rules. Detachment: Once a logical
proof is found for a proposition B, the proposition can be used regardless of
how it was derived .That is, it can be detachment from its justification.
Truth-functionality: In logic, the truth of complex sentences can be computed
from the truth of the components. However, there are no Attachment properties
lies in a Rule-based system. Global attribute defines a particular problem
space as user specific and changes according to user’s plan to problem.
72. How is Fuzzy Logic
different from conventional control methods?
a) IF and THEN Approach
b) FOR Approach
c) WHILE Approach
d) DO Approach
e) Else If approach
Answer: a
Explanation: FL incorporates a simple,
rule-based IF X AND Y THEN Z approach to a solving control problem rather than
attempting to model a system mathematically.
73. In an Unsupervised
learning
a) Specific output values are given
b) Specific output values are not given
c) No specific Inputs are given
d) Both inputs and outputs are given
e) Neither inputs nor outputs are given
Answer: b
Explanation: The problem of unsupervised
learning involves learning patterns in the input when no specific output values
are supplied. We cannot expect the specific output to test your result. Here
the agent does not know what to do, as he is not aware of the fact what propose
system will come out. We can say an ambiguous un-proposed situation.
74. Inductive learning
involves finding a
a) Consistent Hypothesis
b) Inconsistent Hypothesis
c) Regular Hypothesis
d) Irregular Hypothesis
e) Estimated Hypothesis
Answer: a
Explanation: Inductive learning involves
finding a consistent hypothesis that agrees with examples. The difficulty of the
task depends on the chosen representation.
75. Computational
learning theory analyzes the sample complexity and computational complexity of
a) Unsupervised Learning
b) Inductive learning
c) Forced based learning
d) Weak learning
e) Knowledge based learning
Answer: b
Explanation: Computational learning theory
analyzes the sample complexity and computational complexity of inductive
learning. There is a tradeoff between the expressiveness of the hypothesis
language and the ease of learning.
76. If a hypothesis says
it should be positive, but in fact, it is negative, we call it
a) A consistent hypothesis
b) A false negative hypothesis
c) A false positive hypothesis
d) A specialized hypothesis
e) A true positive hypothesis
Answer: c
Explanation: Consistent hypothesis go with
examples, If the hypothesis says it should be negative but infect it is
positive, it is false negative. If a hypothesis says it should be positive, but
in fact, it is negative, it is false positive. In a specialized hypothesis we
need to have certain restrict or special conditions.
77. Neural Networks are
complex ———————–with many parameters.
a) Linear Functions
b) Nonlinear Functions
c) Discrete Functions
d) Exponential Functions
e) Power Functions
Answer: b
Explanation: Neural networks parameters can be
learned from noisy data and they have been used for thousands of applications,
so it varies from problem to problem and thus use nonlinear functions.
78. A perceptron is a
——————————–.
a) Feed-forward neural network
b) Back-propagation algorithm
c) Back-tracking algorithm
d) Feed Forward-backward algorithm
e) Optimal algorithm with Dynamic programming
Answer: a
Explanation: A perceptron is a Feed-forward
neural network with no hidden units that can be representing only linear
separable functions. If the data are linearly separable, a simple weight
updated rule can be used to fit the data exactly.
79. Which of the
following statement is true?
a) Not all formal languages are context-free
b) All formal languages are Context free
c) All formal languages are like natural
language
d) Natural languages are context-oriented free
e) Natural language is formal
Answer: a
Explanation: Not all formal languages are
context-free.
80. Which of the
following statement is not true?
a) The union and concatenation of two
context-free languages is context-free
b) The reverse of a context-free language is
context-free, but the complement need not be
c) Every regular language is context-free
because it can be described by a regular grammar
d) The intersection of a context-free language
and a regular language is always context-free
e) The intersection two context-free languages
is context-free
Answer: e
Explanation: The union and concatenation of two
context-free languages is context-free; but intersection need not be.
81. The process by which
you become aware of messages through your sense is called
a) Organization
b) Sensation
c) Interpretation-Evaluation
d) Perception
Answer: d
82. Susan is so
beautiful; I bet she is smart too. This is an example of
a) The halo effect
b) The primary effect
c) A self-fulfilling prophecy
d) The recency effect
Answer: a
83. _____ prevents you
from seeing an individual as an individual rather than as a member of a group.
a) Cultural mores
b) Stereotypes
c) Schematas
d) Attributions
Answer: c
84. When you get fired
from your job and you determine it is because your boss dislikes you, you are
most likely exhibiting
a) Self-promotion
b) Fundamental attribution error
c) Over-attribution
d) Self-serving bias
Answer: d
85. Mindless processing
is
a) careful, critical thinking
b) inaccurate and faulty processing
c) information processing that relies heavily
on familiar schemata
d) processing that focuses on unusual or novel
events
Answer: c
86. What kind of
perception is used in printing?
a) Optical character recognition
b) Speech recognition
c) Perception
d) None of the mentioned
Answer: a
Explanation: In When perception is used in
printing means, It is called as optical character recognition.
87. Selective retention
occurs when
a) we process, store, and retrieve information
that we have already selected, organized, and interpreted
b) we make choices to experience particular
stimuli
c) we make choices to avoid particular stimuli
d) we focus on specific stimuli while ignoring
other stimuli
Answer: a
88. Which of the
following strategies would NOT be effective at improving your communication
competence?
a) Recognize the people, objects, and
situations remain stable over time
b) Recognize that each person’s frame of
perception is unique
c) Be active in perceiving
d) Distinguish facts from inference
Answer: a
89. _____________ is
measured by the number of mental structures we use, how abstract they are, and
how elaborate they interact to shape our perceptions.
a) intrapersonal structure
b) perceptual set
c) self-justification
d) None of the above
Answer: d
90. A perception check
is
a) a cognitive bias that makes us listen only
to information we already agree with.
b) a method teachers use to reward good
listeners in the classroom.
c) any factor that gets in the way of good
listening and decreases our ability to interpret correctly.
d) a response that allows you to state your
interpretation and ask your partner whether or not that interpretation is
correct.
Answer: d
91. Which provides
agents with information about the world they inhabit?
a) Sense
b) Perception
c) Reading
d) Hearing
Answer: b
Explanation: Perception provides agents with
information about the world they inhabit.
92. What is used to
initiate the perception in the environment?
a) Sensor
b) Read
c) Actuators
d) None of the mentioned
Answer: a
Explanation: A sensor is anything that can
record some aspect of the environment.
93. What is the study of
light?
a) Biology
b) Lightology
c) Photometry
d) All of the mentioned
Answer: c
94. How to increase the
brightness of the pixel?
a) Sound
b) Amount of light
c) Surface
d) Waves
Answer: b
Explanation: The brightness of a pixel in the
image is proportional to the amount of light directed towards the camera.
95. How many kinds of
reflection are available in image perception?
a) 1
b) 2
c) 3
d) 4
Answer: b
Explanation: There are two kinds of
reflection. They are specular and diffuse reflection.
96. What is meant by
predicting the value of a state variable from the past?
a) Specular reflection
b) Diffuse reflection
c) Gaussian filter
d) Smoothing
Answer: d
Explanation: Smoothing meant predicting the
value of a state variable from the past and by given evidence and calculating
the present and future.
97. How many types of
image processing techniques are there in image perception?
a) 1
b) 2
c) 3
d) 4
Answer: c
Explanation: The three image processing
techniques are smoothing, edge detection and image segmentation.
98. Which is meant by
assuming any two neighboring that are both edge pixels with consistent
orientation?
a) Canny edge detection
b) Smoothing
c) Segmentation
d) None of the mentioned
Answer: a
Explanation: Canny edge detection is assuming
any two neighboring that are edge pixels with consistent orientation.
99. What is the process
of breaking an image into groups?
a) Edge detection
b) Smoothing
c) Segmentation
d) None of the mentioned
Answer: c
Explanation: Segmentation is the process of
breaking an image into groups, based on the similarities of the pixels.
100. How many types of
3-D image processing techniques are there in image perception?
a) 3
b) 4
c) 5
d) 6
Answer: c
Explanation: The five types of 3-D image
processing techniques are motion, binocular stereopsis, texture, shading and
contour.
101. Which condition is
used to cease the growth of forward chaining?
a) Atomic sentences
b) Complex sentences
c) No further inference
d) All of the mentioned
Answer:c
Explanation:Forward chain can grow by adding
new atomic sentences until no further inference is made.
102. Which closely
resembles propositional definite clause?
a) Resolution
b) Inference
c) Conjuction
d) First-order definite clauses
Answer:d
Explanation:Because they are disjunction of
literals of which exactly one is positive.
103. What is the
condition of variables in first-order literals?
a) Existentially quantified
b) Universally quantified
c) Both a & b
d) None of the mentioned
Answer:b
Explanation:First-order literals will accept
variables only if they are universally quantified.
104. Which are more
suitable normal form to be used with definite clause?
a) Positive literal
b) Negative literal
c) Generalized modus ponens
d) Neutral literal
Answer:c
Explanation:Definite clauses are a suitable
normal form for use with generalized modus ponen.
105. Which will be the
instance of the class datalog knowledge bases?
a) Variables
b) No function symbols
c) First-order definite clauses
d) None of the mentioned
Answer:b
Explanation:If the knowledge base contains no
function symbols means, it is an instance of the class datalog knowledge base.
106. Which knowledge
base is called as fixed point?
a) First-order definite clause are similar to
propositional forward chaining
b) First-order definite clause are mismatch to
propositional forward chaining
c) Both a & b
d) None of the mentioned
Answer:a
Explanation:Fixed point reached by forward
chaining with first-order definiteclause are similar to those for propositional
forward chaining.
107. How to eliminate
the redundant rule matching attempts in the forward
chaining?
a) Decremental forward chaining
b) Incremental forward chaining
c) Data complexity
d) None of the mentioned
Answer:b
Explanation:We can eliminate the redundant
rule matching attempts in the forward chaining by using incremental forward
chaining.
108. From where did the
new fact inferred on new iteration is derived?
a) Old fact
b) Narrow fact
c) New fact
d) All of the mentioned
Answer:c
109. Which will solve
the conjuncts of the rule so that the total cost is
minimized?
a) Constraint variable
b) Conjunct ordering
c) Data complexity
d) All of the mentioned
Answer:b
Explanation:Conjunct ordering will find an ordering
to solve the conjuncts of the rule premise so that the total cost is minimized.
110. How many possible
sources of complexity are there in forward chaining?
a) 1
b) 2
c) 3
d) 4
Answer:c
Explanation:The three possible sources of
complexity are inner loop, algorithm rechecks every rule on every iteration,
algorithm might generate many facts irrelevant to the goal.
111. Which algorithm
will work backward from the goal to solve a problem?
a) Forward chaining
b) Backward chaining
c) Hill-climb algorithm
d) None of the mentioned
Answer:b
Explanation:Backward chaining algorithm will
work backward from the goal and it will chain the known facts that support the
proof.
112. Which is mainly
used for automated reasoning?
a) Backward chaining
b) Forward chaining
c) Logic programming
d) Parallel programming
Answer:c
Explanation:Logic programming is mainly used
to check the working process of the system.
113. What will backward
chaining algorithm will return?
a) Additional statements
b) Substitutes matching the query
c) Logical statement
d) All of the mentioned
Answer:b
Explanation:It will contains the list of goals
containing a single element and returns the set of all substitutions satisfying
the query.
114. How can be the goal
is thought of in backward chaining algorithm?
a) Queue
b) List
c) Vector
d) Stack
Answer:d
Explanation:The goals can be thought of as
stack and if all of them us satisfied means, then current branch of proof
succeeds.
115. What are used in
backward chaining algorithm?
a) Conjucts
b) Substitution
c) Composition of substitution
d) None of the mentioned
Answer:c
116. Which algorithm are
in more similar to backward chainiing algorithm?
a) Depth-first search algorithm
b) Breadth-first search algorithm
c) Hill-climbing search algorithm
d) All of the mentioned
Answer:a
Explanation:It is depth-first search algorithm
because its space requirements are linear in the size of the proof.
117. Which problem can
frequently occur in backward chaining algorithm?
a) Repeated states
b) Incompleteness
c) Complexity
d) Both a & b
Answer:d
Explanation:If there is any loop in the chain
means, It will lead to incompleteness and repeated states.
118. How the logic
programming can be constructed?
a) Variables
b) Expressing knowledge in a formal language
c) Graph
d) All of the mentioned
Answer:b
Explanation:Logic programming can be
constructed by expressing knowledge in a formal expression and the problem can
be solved by running inference process.
119. What form of
negation does the prolog allows?
a) Negation as failure
b) Proposition
c) Substitution
d) Negation as success
Answer:a
120. Which is omitted in
prolog unification algorithm?
a) Variable check
b) Occur check
c) Proposition check
d) Both b & c
Answer:b
Explanation:Occur check is omitted in prolog
unification algorithm because of unsound inferences.
121. How many issues are
available in describing degree of belief?
a) 1
b) 2
c) 3
d) 4
Answer:b
Explanation:The main issues for degree of
belief are nature of the sentences and the dependance of degree of the belief.
122. What is used for
probability theory sentences?
a) Conditional logic
b) Logic
c) Extension of propositional logic
d) None of the mentioned
Answer:c
Explanation:The version of probability theory
we present uses an extension of propositional logic for its sentences.
123. Where does the
dependance of experience is reflected in prior proability
sentences?
a) Syntactic distinction
b) Semantic distinction
c) Both a & b
d) None of the mentioned
Answer:a
Explanation:The dependance on experience is
reflected in the syntactic distinction between prior probability statements.
124. Where does the
degree of belief are applied?
a) Propositions
b) Literals
c) Variables
d) Statements
Answer:a
125. How many formal
languages are used for stating propositions?
a) 1
b) 2
c) 3
d) 4
Answer:b
Explanation:The two formal languages used for
stating propositions are propositional logic and first-order logic.
126. What is the basic
element for a language?
a) Literal
b) Variable
c) Random variable
d) All of the mentioned
Answer:c
Explanation:The basic element for a langauage
is the random variable, which can be thought as a part of world and its status
is initially unknown.
127. How many types of
random variables are available?
a) 1
b) 2
c) 3
d) 4
Answer:c
Explanation:The three types of random
variables are boolean, discrete and continuous.
128. Which is the
complete specification of the state of the world?
a) Atomic event
b) Complex event
c) Simple event
d) None of the mentioned
Answer:a
Explanation:An atomic event is the complete
specification of the state of the world about which the event is uncertain.
129. Which variable
cannot be written in entire distribution as a table?
a) Discrete
b) Continuous
c) Both a & b
d) None of the mentioned
Answer:b
Explanation:For continuous variables, it is
not posible to write out the entire distribution as a table.
130. What is meant by
probability density function?
a) Probability distributions
b) Continuous variable
c) Discrete variable
d) Probability distributions for Continuous
variables
Answer:d
131. Which is created by
using single propositional symbol?
a) Complex sentences
b) Atomic sentences
c) Composition sentences
d) None of the mentioned
Answer:b
Explanation:Atomic sentences are indivisible
syntactic elements consisting of single propositional symbol.
132. Which is used to
construct the complex sentences?
a) Symbols
b) Connectives
c) Logical connectives
d) All of the mentioned
Answer:c
133. How many
proposition symbols are there in artificial intelligence?
a) 1
b) 2
c) 3
d) 4
Answer:b
Explanation:The two proposition symbols are
true and false.
134. How many logical
connectives are there in artificial intelligence?
a) 2
b) 3
c) 4
d) 5
Answer:d
Explanation:The five logical symbols are
negation, conjuction, disjunction,implication and biconditional.
135. Which is used to
compute the truth of any sentence?
a) Semantics of propositional logic
b) Alpha-beta pruning
c) First-order logic
d) Both a & b
Answer:a
Explanation:Because the meaning of the
sentences is really needed to compute the truth.
136. Which are needed to
compute the logical inference algorithm?
a) Logical equivalence
b) Validity
c) Satisfiability
d) All of the mentioned
Answer:d
Explanation:Logical inference algorithm can be
solved be using logical equivalence, Validity and satisfiability.
137. From which rule
does the modus ponens are derived?
a) Inference rule
b) Module rule
c) Both a & b
d) None of the mentioned
Answer:a
Explanation:Inference rule contains the
standard pattern that leads to desired goal. The best form of inference rule is
modus ponens.
138. Which is also
called single inference rule?
a) Reference
b) Resolution
c) Reform
d) None of the mentioned
Answer:b
Explanation:Because resolution yields a
complete inference rule when coupled with any search algorithm.
139. Which form is
called as conjunction of disjunction of literals?
a) Conjunctive normal form
b) Disjunctive normal form
c) Normal form
d) All of the mentioned
Answer:a
140. What can be viewed
as single leteral of disjunction?
a) Multiple clause
b) Combine clause
c) Unit clause
d) None of the mentioned
Answer:c
Explanation:A single literal can be viewed as
a disjunction or one literal also, called as unit clause.
141. Which is a
refutation complete inference procedure for propositional logic?
a) Clauses
b) Variables
c) Propositional resolution
d) Proposition
Answer: c
Explanation: Propositional resolution is a
refutation complete inference procedure for propositional logic.
142. What kind of
clauses is available in Conjunctive Normal Form?
a) Disjunction of literals
b) Disjunction of variables
c) Conjunction of literals
d) Conjunction of variables
Answer: a
Explanation: First-order resolution requires
the clause to be in disjunction of literals in Conjunctive Normal Form.
143. What is the
condition of literals in variables?
a) Existentially quantified
b) Universally quantified
c) Quantified
d) None of the mentioned
Answer: b
Explanation: Literals that contain variables
are assumed to be universally quantified.
144. Which can be
converted to inferred equivalent CNF (Conjunction Normal Form) sentence?
a) Every sentence of propositional logic
b) Every sentence of inference
c) Every sentence of first-order logic
d) All of the mentioned
Answer: c
Explanation: Every sentence of first-order
logic can be converted to inferred equivalent CNF(Conjunction Normal Form)
sentence.
145. Which sentence will
be unsatisfiable if the CNF (Conjunction Normal Form) sentence is
unsatisfiable?
a) Search statement
b) Reading statement
c) Replaced statement
d) Original statement
Answer: d
Explanation: The CNF statement will be
unsatisfiable just when the original sentence is unsatisfiable.
146. Which rule is equal
to resolution rule of first-order clauses?
a) Propositional resolution rule
b) Inference rule
c) Resolution rule
d) None of the mentioned
Answer: a
Explanation: The resolution rule for
first-order clauses is simply a lifted version of the propositional resolution
rule.
147. At which state does
the propositional literals are complementary.
a) If one variable is less
b) If one is the negation of the other
c) Both a & b
d) None of the mentioned
Answer: b
Explanation: Propositional literals are
complementary if one is the negation of the other.
148. What is meant by
factoring?
a) Removal of redundant variable
b) Removal of redundant literal
c) Addition of redundant literal
d) Addition of redundant variable
Answer: b
149. What will happen if
two literals are identical?
a) Remains the same
b) Added as three
c) Reduced to one
d) None of the mentioned
Answer: c
Explanation: Propositional factoring reduces
two literals to one if they are identical.
150. When the resolution
is called as refutation-complete?
a) Sentence is satisfiable
b) Sentence is unsatisfiable
c) Sentence remains the same
d) None of the mentioned
Answer: b
Explanation: Resolution is
refutation-complete, if a set of sentence is unsatisfiable, then resolution
will always be able to derive a contradiction.
151. Computers normally
solve problem by breaking them down into a series of yes-or-no decisions
represented by 1s and 0s. What is the name of the logic that allows computers
to assign numerical values that fail somewhere between 0 and 1?
a) Human logic
b) Fuzzy logic
c) Boolean logic
d) Operational logic
Answer: b
152. The component of an
ICAI (Intelligent Computer-Asslsted Instruction) presenting information to the
student is the:
a) student model
b) problem-solving expertise
c) tutoring module
d) All of the mentioned
Answer: c
153. The company that
grew out of research at the MIT AI lab is:
a) AI corp
b) LMI
c) Symbolics
d) both b & c
Answer: d
154. Which technique is
being investigated as an approach to automatic programming?
a) generative CAI
b) specification by example
c) All of the above
d) non-hierarchical planning
Answer: b
155. One definition of
AI focuses on problem-solving methods that process:
a) smell
b) symbols
c) touch
d) algorithms
Answer: b
156. Artificial
intelligence is
a) the embodiment of human intellectual
capabilities within a computer.
b) a set of computer programs that produce
output that would be considered to reflect intelligence if it were generated by
humans.
c) the study of mental faculties through the
use of mental models implemented on a computer.
d) All of the mentioned
Answer: d
157. The primary method
that people use to sense their environment is:
a) reading
b) writing
c) speaking
d) seeing
Answer: d
158. The Newell and
Simon program that proved theorems of Principia Mathematica was:
a) Elementary Perceiver
b) General Problem Solver
c) Logic Theorist
d) Boolean Algebra
Answer: c
159. In LISP, the
function assigns . the value of a to b is
a) (setq a b)
b) (setq b a )
c) (b = a)
d) (set b = a)
Answer: b
160. The cray X-MP, IBM
3090 and connection machine can he characterized as
a) SISD
b) SIMD
c) MISD
d) MIMD
Answer: b
161. Ambiguity may be
caused by:
a) syntactic ambiguity
b) multiple word meanings
c) unclear antecedents
d) All of the mentioned
Answer: d
162. Which company
offers the LISP machine considered to be “the most powerful symbolic processor
available”?
a) LMI
b) Symbolics
c) Xerox
d) Texas Instruments
Answer: b
163. What of the
following is considered to be a pivotal event in the history of Artificial
Intelligence.
a) 1949, Donald O, The organization of
Behavior,
b) 1950, Computing Machinery and Intelligence.
c) 1956, Dartmouth University Conference
Organized by John McCarthy
d) 1961, Computer and Computer Sense.
Answer: c
164. Natural language
processing is divided into the two subfields of:
a) symbolic and numeric
b) time and motion
c) algorithmic and heuristic
d) understanding and generation
Answer: d
165. High-resolution,
bit-mapped displays are useful for displaying:
a) clearer characters
b) graphics
c) more characters
d) All of the mentioned
Answer: d
166. A bidirectional
feedback loop links computer modeling with:
a) artificial science
b) heuristic processing
c) human intelligence
d) cognitive science
Answer: d
167. Which of the
following have people traditionally done better than computers?
a) recognizing relative importance
b) finding similarities
c) resolving ambiguity
Answer: d
168. In LISP, the
function evaluates both and is
a) set
b) setq
c) add
d) eva
Answer: a
169. What takes input as
an object described bya set of attributes?
a) Tree
b) Graph
c) Decision graph
d) Decision tree
Answer: d
170. How the decision
tree reaches its decision?
a) Single test
b) Two test
c) Sequence of test
d) No test
Answer: c
171. Ambiguity may be
caused by:
a) syntactic ambiguity
b) multiple word meanings
c) unclear antecedents
d) All of the mentioned
Answer: d
172. Which company
offers the LISP machine considered “the most powerful symbolic processor
available”?
a) LMI
b) Symbolics
c) Xerox
d) Texas Instruments
Answer: b
173. What of the
following is considered a pivotal event in the history of Artificial
Intelligence?
a) 1949, Donald O, The organization of
Behavior
b) 1950, Computing Machinery and Intelligence
c) 1956, Dartmouth University Conference
Organized by John McCarthy
d) 1961, Computer and Computer Sense
Answer: c
174. Natural language
processing is divided into the two sub-fields of:
a) symbolic and numeric
b) time and motion
c) algorithmic and heuristic
d) understanding and generation
Answer: c
175. High-resolution,
bit-mapped displays are useful for displaying:
a) clearer characters
b) graphics
c) more characters
d) All of the mentioned
Answer: c
176. A bidirectional
feedback loop links computer modeling with:
a) artificial science
b) heuristic processing
c) human intelligence
d) cognitive science
Answer: c
177. Which of the
following have people traditionally done better than computers?
a) recognizing relative importance
b) finding similarities
c) resolving ambiguity
d) All of the above
Answer: c
178. In LISP, the
function evaluates both and is
a) set
b) setq
c) add
d) eva
Answer: a
179. Which type of
actuator generates a good deal of power but tends to be messy?
a) electric
b) hydraulic
c) pneumatic
d) Both b & c
Answer: b
180. Research scientists
all over the world are taking steps towards building computers with circuits
patterned after the complex inter connections existing among the human brain’s
nerve cells. What name is given to such type of computers?
a) Intelligent computers
b) Supercomputers
c) Neural network computers
d) Smart computers
Answer: c
181.Which search is
equal to minimax search but eliminates the branchesthat can’t influence the
final decision?
a) Depth-first search
b) Breadth-first search
c) Alpha-beta pruning
d) None of the mentioned
Answer: c
182. Which values are independant in minimax
search algorithm?
a) Pruned leaves x and y
b) Every states are dependant
c) Root is independant
d) None of the mentioned
Answer: a
183.To which depth does
the alpha-beta pruning can be applied?
a) 10 states
b) 8 States
c) 6 States
d) Any depth
Answer: d
184.Which search is
similar to minimax search?
a) Hill-climbing search
b) Depth-first search
c) Breadth-first search
d) All of the mentioned
Answer: b
185.Which value is
assigned to alpha and beta in the alpha-beta pruning?
a) Alpha = max
b) Beta = min
c) Beta = max
d) Both a & b
Answer: d
186.Where does the
values of alpha-beta search get updated?
a) Along the path of search
b) Initial state itself
c) At the end
d) None of the mentioned
Answer: a
187.How the
effectiveness of the alpha-beta pruning gets increased?
a) Depends on the nodes
b) Depends on the order in which they are
executed
c) Both a & b
d) None of the mentioned
Answer: a
188.What is called as
transposition table?
a) Hash table of next seen positions
b) Hash table of previously seen positions
c) Next value in the search
d) None of the mentioned
Answer: b
189.Which is identical
to the closed list in Graph search?
a) Hill climbing search algorithm
b) Depth-first search
c) Transposition table
d) None of the mentioned
Answer: c
190.Which function is
used to calculate the feasibility of whole game tree?
a) Evaluation function
b) Transposition
c) Alpha-beta pruning
d) All of the mentioned
Answer: a
191.What is the action
of task environment in artificial intelligence?
a) Problem
b) Solution
c) Agent
d) Observation
Answer: a
192.What is the
expansion if PEAS in task environment?
a) Peer, Environment, Actuators, Sense
b) Perceiving, Enivornment, Actuators, Sensors
c) Performance, Environment, Actuators,
Sensors,
d) None of the mentioned
Answer: c
193.What kind of observing
environments are present in artificial intelligence?
a) Partial
b) Fully
c) Learning
d) Both a & b
Answer: d
194.What kind of
environment is strategic in artificial intelligence?
a) Deterministic
b) Rational
c) Partial
d) Stochastic
Answer: a
195.What kind of
environment is crossword puzzle?
a) Static
b) Dynamic
c) Semidynamic
d) None of the mentioned
Answer: a
196.What kind of
behavior does the stochastic environment posses?
a) Local
b) Deterministic
c) Ratioanl
d) Primary
Answer: a
197.Which is used to
select the particular environment to run the agent?
a) Environment creator
b) Environment Generator
c) Both a & b
d) None of the mentioned
Answer: b
198.Which environment is
called as semidynamic?
a) Environment does not change with the
passage of time
b) Agent performance changes
c) Environment will be changed
d) Both a & b
Answer: d
199.Where does the
performance measure is included?
a) Rational agent
b) Task environment
c) Actuators
d) Sensor
Answer: b
200.Which is used to
provide the feedback to the learning element?
a) Critic
b) Actuators
c) Sensor
d) None of the mentioned
Answer: a
201.Given a stream of
text, Named Entity Recognition determines which pronoun maps to which noun.
a) False
b) True
Answer: a
202.Natural Language
generation is the main task of Natural language processing.
a) True
b) False
Answer: a
203.OCR (Optical
Character Recognition) uses NLP.
a) True
b) False
Answer: a
204.Parts-of-Speech
tagging determines
a) part-of-speech for each word
b) part-of-speech for each word dynamically as
per sentence structure and meaning
c) all part-of-speech for a specific word
given as input
d) all of the mentioned
Answer: b, c
205.Parsing determines
Parse Trees (Grammatical Analysis) for a given sentence.
a) True
b) False
Answer: a
206.IR (information
Retrieval) and IE (Information Extraction) are the two same thing.
a) True
b) False
Answer: b
207.Many words have more
than one meaning; we have to select the meaning which makes the most sense in
context. This can be resolved by
a) Fuzzy Logic
b) Word Sense Disambiguation
c) Shallow Semantic Analysis
d) All of the mentioned
Answer: b
208.Given a sound clip
of a person or people speaking, determine the textual representation of the
speech.
a) Text-to-speech
b) Speech-to-text
Answer: b
209.Speech Segmentation
is a subtask of Speech Recognition.
a) True
b) False
Answer: a
210. In linguistic
morphology, _____________ is the process for reducing inflected words to their
root form.
a) Rooting
b) Stemming
c) Text-Proofing
d) Both a & b
Answer: b
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