Recent questions tagged artificial-intelligence

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1

UGCNET-Jan2017-III: 72
A neuron with $3$ inputs has the weight vector $\begin{bmatrix} 0.2 & -0.1 & 0.1 \end{bmatrix}^{T}$ and a bias $\theta =0.$ If the input vector is $X=\begin{bmatrix} 0.2 & 0.4 & 0.2 \end{bmatrix}^{T}$ then the total input to the neuron is: $0.20$ $1.0$ $0.02$ $-1.0$

A neuron with $3$ inputs has the weight vector $\begin{bmatrix} 0.2 & -0.1 & 0.1 \end{bmatrix}^{T}$ and a bias $\theta =0.$ If the input vector is $X=\begin{bmatrix} 0.2 & 0.4 & 0.2 \end{bmatrix}^{T}$ then the total input to the neuron is: $0.20$ $1.0$ $0.02$ $-1.0$

asked Mar 24 in Artificial Intelligence jothee 81 views

2 votes

1 answer

2

UGCNET-June-2019-II: 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 $4$ $7$ $11$ $12$

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 $4$ $7$ $11$ $12$

asked Jul 2, 2019 in Artificial Intelligence Arjun 781 views

1 vote

1 answer

3

UGCNET-June-2019-II: 92
Math List-I with List-II: ... (ii); (c) - (i) (a) - (i) ; (b) - (iii); (c) - (ii) (a) - (ii) ; (b) - (iii); (c) - (i)

Math List-I with List-II: ... ) ; (b) - (ii); (c) - (i) (a) - (i) ; (b) - (iii); (c) - (ii) (a) - (ii) ; (b) - (iii); (c) - (i)

asked Jul 2, 2019 in Artificial Intelligence Arjun 500 views

1 vote

1 answer

4

UGCNET-June-2019-II: 93
The STRIPS representation is a feature-centric representation an action-centric representation a combination of feature-centric and action-centric representations a hierarchical feature-centric representation

The STRIPS representation is a feature-centric representation an action-centric representation a combination of feature-centric and action-centric representations a hierarchical feature-centric representation

asked Jul 2, 2019 in Artificial Intelligence Arjun 696 views

1 vote

1 answer

5

UGCNET-June-2019-II: 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: $t(x,y) = 1-s(x,y)$ $t(x,y) = s(1-x,1-y)$ $t(x,y) = 1-s(1-x,1-y)$ $t(x,y) = s(1+x,1+y)$

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: $t(x,y) = 1-s(x,y)$ $t(x,y) = s(1-x,1-y)$ $t(x,y) = 1-s(1-x,1-y)$ $t(x,y) = s(1+x,1+y)$

asked Jul 2, 2019 in Artificial Intelligence Arjun 902 views

1 vote

2 answers

6

UGCNET-June-2019-II: 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

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

asked Jul 2, 2019 in Artificial Intelligence Arjun 780 views

2 votes

1 answer

7

UGCNET-June-2019-II: 98
Which of the following is an example of unsupervised neural network? Back-propagation network Hebb network Associative memory network Self-organizing feature map

Which of the following is an example of unsupervised neural network? Back-propagation network Hebb network Associative memory network Self-organizing feature map

asked Jul 2, 2019 in Artificial Intelligence Arjun 498 views

2 votes

1 answer

8

UGCNET-June-2019-II: 99
The value of the derivative of Sigmoid function given by $f(x)=\dfrac{1}{1+e^{-2x}}$ at $x=0$ is $0$ $\frac{1}{2}$ $\frac{1}{4}$ $\infty$

The value of the derivative of Sigmoid function given by $f(x)=\dfrac{1}{1+e^{-2x}}$ at $x=0$ is $0$ $\frac{1}{2}$ $\frac{1}{4}$ $\infty$

asked Jul 2, 2019 in Artificial Intelligence Arjun 517 views

1 vote

1 answer

9

UGCNET-June-2019-II: 100
Reinforcement learning can be formalized in terms of ____ in which the agent initially only knows the set of possible _____ and the set of possible actions. Markov decision processes, objects Hidden states, objects Markov decision processes, states objects, states

Reinforcement learning can be formalized in terms of ____ in which the agent initially only knows the set of possible _____ and the set of possible actions. Markov decision processes, objects Hidden states, objects Markov decision processes, states objects, states

asked Jul 2, 2019 in Artificial Intelligence Arjun 385 views

4 votes

0 answers

10

MTech and machine learning
I am a dropper and have worked an year on machine learning in the industry. I want to do learn more about ML/AI and image processing. I am getting a rank around 200(from GO rank predictor). I am open to 2 or 3 year courses and any college is fine as long as I get to work in my field of interest and the resources are good there. What are the best options for me?

I am a dropper and have worked an year on machine learning in the industry. I want to do learn more about ML/AI and image processing. I am getting a rank around 200(from GO rank predictor). I am open to 2 or 3 year courses and any college is fine as long as I get to work in my field of interest and the resources are good there. What are the best options for me?

asked Feb 10, 2019 in IISc/IITs subho16 327 views

0 votes

2 answers

11

UGCNET-July-2018-II: 71
In artificial Intelligence (AI), an environment is uncertain if it is ___ Not fully observable and not deterministic Not fully observable or not deterministic Fully observable but not deterministic Not fully observable but deterministic

In artificial Intelligence (AI), an environment is uncertain if it is ___ Not fully observable and not deterministic Not fully observable or not deterministic Fully observable but not deterministic Not fully observable but deterministic

asked Jul 13, 2018 in Artificial Intelligence Pooja Khatri 604 views

0 votes

2 answers

12

UGCNET-July-2018-II: 72
In artificial Intelligence (AI), a simple reflex agent selects actions on the basis of ___ current percept, completely ignoring rest of the percept history rest of the percept history, completely ignoring the current percept both current percept and complete percept history both current percept and just previous percept

In artificial Intelligence (AI), a simple reflex agent selects actions on the basis of ___ current percept, completely ignoring rest of the percept history rest of the percept history, completely ignoring the current percept both current percept and complete percept history both current percept and just previous percept

asked Jul 13, 2018 in Artificial Intelligence Pooja Khatri 658 views

0 votes

1 answer

13

UGCNET-July-2018-II: 73
In heuristic search algorithms in Artificial Intelligence (AI), if a collection of admissible heuristics $h_1 \dots h_m$ is available for a problem and none of them dominates any of the others, which should we choose? $h(n)=max\{h_1(n), \dots , h_m(n)\}$ $h(n)=min\{h_1(n), \dots , h_m(n)\}$ $h(n)=avg\{h_1(n), \dots , h_m(n)\}$ $h(n)=sum\{h_1(n), \dots , h_m(n)\}$

In heuristic search algorithms in Artificial Intelligence (AI), if a collection of admissible heuristics $h_1 \dots h_m$ is available for a problem and none of them dominates any of the others, which should we choose? $h(n)=max\{h_1(n), \dots , h_m(n)\}$ $h(n)=min\{h_1(n), \dots , h_m(n)\}$ $h(n)=avg\{h_1(n), \dots , h_m(n)\}$ $h(n)=sum\{h_1(n), \dots , h_m(n)\}$

asked Jul 13, 2018 in Artificial Intelligence Pooja Khatri 884 views

0 votes

1 answer

14

UGCNET-July-2018-II: 74
Consider following sentences regarding $A^*$, an informed search strategy in Artificial Intelligence (AI). $A^*$ expands all nodes with $f(n)<C^*$ $A^*$ expands no nodes with $f(n) \geq C^*$ Pruning is integral to $A^*$ Here, $C^*$ is ... b are true Both statements a and statement c are true Both statements b and statement c are true All the statements a, b and c are true

Consider following sentences regarding $A^*$, an informed search strategy in Artificial Intelligence (AI). $A^*$ expands all nodes with $f(n)<C^*$ $A^*$ expands no nodes with $f(n) \geq C^*$ Pruning is integral to $A^*$ Here, $C^*$ is the cost of ... statement b are true Both statements a and statement c are true Both statements b and statement c are true All the statements a, b and c are true

asked Jul 13, 2018 in Artificial Intelligence Pooja Khatri 711 views

0 votes

2 answers

15

Uttrakhand Asst. Professor Exam-95
Which condition is used to influence a variable directly by all the others Partially Connected Full Connected Local Connected None of the above

Which condition is used to influence a variable directly by all the others Partially Connected Full Connected Local Connected None of the above

asked Mar 2, 2018 in Unknown Category gatecse 109 views

0 votes

1 answer

16

Uttrakhand Asst. Professor Exam-20
Which agent enables the deliberation about the computational entities and actions ? Hybrid Reflective Relational None of the above

Which agent enables the deliberation about the computational entities and actions ? Hybrid Reflective Relational None of the above

asked Mar 2, 2018 in Unknown Category gatecse 124 views

0 votes

1 answer

17

Uttrakhand Asst. Professor Exam-17
Which of the following is a method of analogical problem solving that have been studied in AI ? Transformational analogy Derivational analogy Both A and B None of the above

Which of the following is a method of analogical problem solving that have been studied in AI ? Transformational analogy Derivational analogy Both A and B None of the above

asked Mar 2, 2018 in Unknown Category gatecse 67 views

0 votes

1 answer

18

Uttrakhand Asst. Professor Exam-18
What is Artificial Intelligence ? Putting your intelligence into computer Programming with your own intelligence Making a machine intelligent Putting more memory into computer

What is Artificial Intelligence ? Putting your intelligence into computer Programming with your own intelligence Making a machine intelligent Putting more memory into computer

asked Mar 2, 2018 in Unknown Category gatecse 57 views

1 vote

1 answer

19

UGC NET JULY 2016
A perceptron has input weights W1 = -3.9 and W2 = 1.1 with threshold value T = 0.3. What output does it give for the input x1 = 1.3 and x2 = 2.2? (A) -2.65 (B) -2.30 (B) 0 (D) 1

A perceptron has input weights W1 = -3.9 and W2 = 1.1 with threshold value T = 0.3. What output does it give for the input x1 = 1.3 and x2 = 2.2? (A) -2.65 (B) -2.30 (B) 0 (D) 1

asked Nov 2, 2017 in Others Naqvi 646 views

0 votes

2 answers

20

UGCNET-June2014-III: 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

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

asked Jan 5, 2017 in Artificial Intelligence jothee 817 views

1 vote

3 answers

21

UGCNET-AUG2016-III: 75
Which formal system provides the semantic foundation for Prolog ? Predicate calculus Lambda calculus Hoare logic Propositional logic

Which formal system provides the semantic foundation for Prolog ? Predicate calculus Lambda calculus Hoare logic Propositional logic

asked Oct 5, 2016 in Others makhdoom ghaya 1.6k views

1 vote

1 answer

22

UGCNET-AUG2016-III: 73
Criticism free idea generation is a factor of _____. Decision Support System Group Decision Support System Enterprise Resource Support System Artificial Intelligence

Criticism free idea generation is a factor of _____. Decision Support System Group Decision Support System Enterprise Resource Support System Artificial Intelligence

asked Oct 5, 2016 in Data Mining and Warehousing makhdoom ghaya 825 views

2 votes

1 answer

23

UGCNET-AUG2016-III: 72
In Artificial Intelligence , a semantic network Is a graph-based method of knowledge representation where nodes represent concepts and arcs represent relations between concepts. Is a graph-based method of knowledge representation where nodes represent relations between ... . Represents an entity as a set of slots and associated rules. Is a subset of first-order logic.

In Artificial Intelligence , a semantic network Is a graph-based method of knowledge representation where nodes represent concepts and arcs represent relations between concepts. Is a graph-based method of knowledge representation where nodes represent relations between concepts and arcs ... concepts. Represents an entity as a set of slots and associated rules. Is a subset of first-order logic.

asked Oct 5, 2016 in Others makhdoom ghaya 606 views

2 votes

1 answer

24

UGCNET-AUG2016-III: 71
Match each Artificial Intelligence term in List-I that best describes a given situation in List - II : List - I List - II I. Semantic Network a. Knowledge about what to do as opposed to how to do it. II. Frame b. A premise of a rule that is not concluded by any rule. III. Declarative ... Codes : I II III IV d a b c d c a b d c b a c d a b

Match each Artificial Intelligence term in List-I that best describes a given situation in List - II : List - I List - II I. Semantic Network a. Knowledge about what to do as opposed to how to do it. II. Frame b. A premise of a rule that is not concluded by any rule. III. Declarative knowledge c. A method of ... Codes : I II III IV d a b c d c a b d c b a c d a b

asked Oct 5, 2016 in Others makhdoom ghaya 592 views

3 votes

2 answers

25

UGCNET-June2016-III: 74
Consider a 3-puzzle where, like in the usual 8-puzzle game, a tile can only move to an adjacent empty space. Given the initial state 1 2 3 which of the following state cannot be reached? A 3 1 2 B 3 2 1 C 1 3 2 D 2 1 3

Consider a 3-puzzle where, like in the usual 8-puzzle game, a tile can only move to an adjacent empty space. Given the initial state 1 2 3 which of the following state cannot be reached? A 3 1 2 B 3 2 1 C 1 3 2 D 2 1 3

asked Aug 21, 2016 in Others jothee 2k views

3 votes

1 answer

26

UGCNET-June2016-III: 72
How does randomized Hill climbing choose the next move each time? It generates a random move from moveset and accepts this move It generates random move from whole state space, and accepts this move It generates a random move from moveset and ... It generates a random move from whole state space, and accepts this move only if this move improves the evaluation function

How does randomized Hill climbing choose the next move each time? It generates a random move from moveset and accepts this move It generates random move from whole state space, and accepts this move It generates a random move from moveset and accepts this move ... function It generates a random move from whole state space, and accepts this move only if this move improves the evaluation function

asked Aug 21, 2016 in Others jothee 1.4k views

2 votes

1 answer

27

UGCNET-Dec2015-III: 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: $x_1-x_2-0.5=0$ $-x_1-x_2-0.5=0$ $0.5(x_1+x_2)-1.5=0$ $x_1+x_2-0.5=0$

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: $x_1-x_2-0.5=0$ $-x_1-x_2-0.5=0$ $0.5(x_1+x_2)-1.5=0$ $x_1+x_2-0.5=0$

asked Aug 11, 2016 in Artificial Intelligence jothee 2.3k views

3 votes

1 answer

28

UGCNET-Dec2015-III: 46
Language model used in LISP is Functional programming Logic programming Object oriented programming All of the above

Language model used in LISP is Functional programming Logic programming Object oriented programming All of the above

asked Aug 11, 2016 in Artificial Intelligence jothee 1k views

1 vote

1 answer

29

UGCNET-Dec2015-III: 45
Reasoning strategies used in expert systems include Forward chaining, backward chaining and problem reduction Forward chaining, backward chaining and boundary mutation Forward chaining, backward chaining and back propagation Forward chaining, problem reduction and boundary mutation

Reasoning strategies used in expert systems include Forward chaining, backward chaining and problem reduction Forward chaining, backward chaining and boundary mutation Forward chaining, backward chaining and back propagation Forward chaining, problem reduction and boundary mutation

asked Aug 11, 2016 in Data Mining and Warehousing jothee 1.2k views

3 votes

1 answer

30

UGCNET-Dec2015-III: 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

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

asked Aug 9, 2016 in Artificial Intelligence jothee 2k views

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