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Most viewed questions in Artificial Intelligence
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UGC NET CSE | December 2012 | Part 2 | Question: 46
Back propagation is a learning technique that adjusts weights in the neutral network by propagating weight changes. Forward from source to sink Backward from sink to source Forward from source to hidden nodes Backward from sink to hidden nodes
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Artificial Intelligence
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go_editor
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ugcnetcse-dec2012-paper2
machine-learning
data-mining
back-propagation
1
vote
2
answers
2
UGC NET CSE | June 2019 | Part 2 | Question: 97
Consider the following: Evolution Selection Reproduction Mutation Which of the following are found in genetic algorithms? b, c and d only b and d only a, b, c and d a, b and d only
Arjun
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Artificial Intelligence
Jul 2, 2019
by
Arjun
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ugcnetcse-june2019-paper2
artificial-intelligence
genetic-algorithms
3
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2
answers
3
UGC NET CSE | December 2015 | Part 3 | Question: 8
Forward chaining systems are ____ where as backward chaining systems are ____ Data driven, Data driven Goal driven, Data driven Data driven, Goal driven Goal driven, Goal driven
go_editor
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Artificial Intelligence
Aug 9, 2016
by
go_editor
5.6k
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ugcnetcse-dec2015-paper3
artificial-intelligence
chaining
0
votes
1
answer
4
UGC NET CSE | December 2013 | Part 3 | Question: 30
An artificial neuron receives n inputs $x_1, x_2, \dots , x_n$ with weights $w_1, w_2, \dots , w_n$ attached to the input links. The weighted sum ____ is computed to be passed on to a non-linear filter $\phi$ called activation function to release the output ... $\Sigma \: x_i$ $\Sigma \: w_i + \Sigma \: x_i$ $\Sigma \: w_i \cdot \Sigma \: x_i$
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Artificial Intelligence
Jul 28, 2016
by
go_editor
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ugcnetcse-dec2013-paper3
machine-learning
artificial-neural-network
3
votes
2
answers
5
UGC NET CSE | June 2012 | Part 3 | Question: 2
In Delta Rule for error minimization weights are adjusted w.r.to change in the output weights are adjusted w.r.to difference between desired output and actual output weights are adjusted w.r.to difference between output and output none of the above
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Artificial Intelligence
Jul 6, 2016
by
go_editor
5.1k
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ugcnetcse-june2012-paper3
artificial-intelligence
machine-learning
1
vote
2
answers
6
UGC NET CSE | December 2012 | Part 3 | Question: 73
Match the following: a. Supervised learning 1. The decision system receives rewards for its action at the end of a sequence of steps b. Unsupervised learning 2. Manual labels of inputs are not used c. Re-inforcement learning 3. Manual labels of inputs are used d. Inductive learning 4 ... by example a b c d A 1 2 3 4 B 2 3 1 4 C 3 2 4 1 D 3 2 1 4
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Artificial Intelligence
Jul 13, 2016
by
go_editor
4.8k
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ugcnetcse-dec2012-paper3
machine-learning
3
votes
1
answer
7
UGC NET CSE | December 2014 | Part 3 | Question: 72
Match the following learning modes $w.r.t$. characteristics of available information for learning : a. Supervised i. Instructive information on desired responses, explicitly specified by a teacher. b. Recording ii. A priori design information for memory storing c. Reinforcement ... Codes : a b c d i ii iii iv i iii ii iv ii iv iii i ii iii iv i
makhdoom ghaya
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Artificial Intelligence
Aug 2, 2016
by
makhdoom ghaya
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ugcnetcse-dec2014-paper3
artificial-intelligence
machine-learning
1
vote
2
answers
8
UGC NET CSE | June 2014 | Part 3 | Question: 09
Perceptron learning, Delta learning and $LMS$ learning are learning methods which falls under the category of Error correction learning - learning with a teacher Reinforcement learning - learning with a critic Hebbian learning Competitive learning - learning without a teacher
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Artificial Intelligence
Jul 4, 2016
by
makhdoom ghaya
4.6k
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ugcnetjune2014iii
machine-learning
2
votes
1
answer
9
UGC NET CSE | December 2015 | Part 3 | Question: 64
Consider the two class classification task that consists of the following points: Class $C_1: [-1, -1], [-1, 1], [1, -1]$ Class $C_2: [1,1]$ The decision boundary between the two classes $C_1$ and $C_2$ using single perception is given by: $x_1-x_2-0.5=0$ $-x_1-x_2-0.5=0$ $0.5(x_1+x_2)-1.5=0$ $x_1+x_2-0.5=0$
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Artificial Intelligence
Aug 11, 2016
by
go_editor
4.6k
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ugcnetcse-dec2015-paper3
artificial-intelligence
1
vote
2
answers
10
UGC NET CSE | June 2012 | Part 3 | Question: 21
$A^*$ algorithm uses $f'=g+h'$ to estimate the cost of getting from the initial state to the goal state, where $g$ is a measure of cost getting from initial state to the current node and the function $h'$ is an estimate of the cost of getting from the ... . To find a path involving the fewest number of steps, we should test, $g=1$ $g=0$ $h'=0$ $h'=1$
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Artificial Intelligence
Jul 7, 2016
by
go_editor
4.4k
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ugcnetcse-june2012-paper3
artificial-intelligence
3
votes
3
answers
11
ISRO2011-2
Which of the following is an unsupervised neural network? RBS Hopfield Back propagation Kohonen
Anuanu
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Artificial Intelligence
Jun 15, 2016
by
Anuanu
4.4k
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isro2011
neural-network
non-gate
1
vote
1
answer
12
UGC NET CSE | September 2013 | Part 3 | Question: 5
The Blocks World Problem in Artificial Intelligence is normally discussed to explain a Search technique Planning system Constraint satisfaction system Knowledge base system
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Artificial Intelligence
Jul 22, 2016
by
go_editor
4.3k
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ugcnetcse-sep2013-paper3
artificial-intelligence
blocks-world-problem
0
votes
2
answers
13
UGC NET CSE | June 2014 | Part 3 | Question: 14
Which one of the following describes the syntax of prolog program? Rules and facts are terminated by full stop(.) Rules and facts are terminated by semi colon(;) Variables names must start with upper case alphabets. Variables names must start with lower case alphabets. I, II III, IV I, III II, IV
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Artificial Intelligence
Jan 5, 2017
by
go_editor
4.0k
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ugcnetjune2014iii
artificial-intelligence
prolog
1
vote
1
answer
14
UGC NET CSE | September 2013 | Part 3 | Question: 6
Means-Ends Analysis process centres around the detection of difference between the current state and the goal state. Once such a difference is found, then to reduce the difference one applies a forward search that can ... can reduce the difference a bidirectional search that can reduce the difference an operator that can reduce the difference
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Artificial Intelligence
Jul 22, 2016
by
go_editor
3.6k
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ugcnetcse-sep2013-paper3
artificial-intelligence
means-end
analysis
0
votes
2
answers
15
UGC NET CSE | June 2014 | Part 3 | Question: 30
Slots and facets are used in Semantic Networks Frames Rules All of these
makhdoom ghaya
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in
Artificial Intelligence
Jul 9, 2016
by
makhdoom ghaya
3.5k
views
ugcnetjune2014iii
artificial-intelligence
1
vote
1
answer
16
UGC NET CSE | June 2019 | Part 2 | Question: 94
A fuzzy conjunction operator denoted as $t(x,y)$ and a fuzzy disjunction operator denoted as $s(x,y)$ form a dual pair if they satisfy the condition: $t(x,y) = 1-s(x,y)$ $t(x,y) = s(1-x,1-y)$ $t(x,y) = 1-s(1-x,1-y)$ $t(x,y) = s(1+x,1+y)$
Arjun
asked
in
Artificial Intelligence
Jul 2, 2019
by
Arjun
3.4k
views
ugcnetcse-june2019-paper2
artificial-intelligence
fuzzy-logic
0
votes
1
answer
17
UGC NET CSE | September 2013 | Part 3 | Question: 28
In a single perceptron, the updation rule of weight vector is given by $w(n+1) = w(n) + \eta [d(n)-y(n)]$ $w(n+1) = w(n) - \eta [d(n)-y(n)]$ $w(n+1) = w(n) + \eta [d(n)-y(n)]*x(n)$ $w(n+1) = w(n) - \eta [d(n)-y(n)]*x(n)$
go_editor
asked
in
Artificial Intelligence
Jul 24, 2016
by
go_editor
3.2k
views
ugcnetcse-sep2013-paper3
neural-network
machine-learning
2
votes
1
answer
18
UGC NET CSE | June 2019 | Part 2 | Question: 91
Consider the game tree given below: Here $\bigcirc$ and $\Box$ represents MIN and MAX nodes respectively. The value of the root node of the game tree is $4$ $7$ $11$ $12$
Arjun
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in
Artificial Intelligence
Jul 2, 2019
by
Arjun
3.1k
views
ugcnetcse-june2019-paper2
artificial-intelligence
minimax-procedure
2
votes
1
answer
19
UGC NET CSE | June 2019 | Part 2 | Question: 98
Which of the following is an example of unsupervised neural network? Back-propagation network Hebb network Associative memory network Self-organizing feature map
Arjun
asked
in
Artificial Intelligence
Jul 2, 2019
by
Arjun
3.1k
views
ugcnetcse-june2019-paper2
artificial-intelligence
neural-network
2
votes
1
answer
20
UGC NET CSE | June 2013 | Part 3 | Question: 71
The map colouring problem can be solved using which of the following technique? Means-end analysis Constraint satisfaction AO* search Breadth first search
go_editor
asked
in
Artificial Intelligence
Jul 19, 2016
by
go_editor
3.1k
views
ugcnetcse-june2013-paper3
artificial-intelligence
map-coloring
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