# Recent questions tagged artificial-intelligence

1
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: $0.20$ $1.0$ $0.02$ $-1.0$
2
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 $4$ $7$ $11$ $12$
1 vote
3
Math List-I with List-II: ... ) ; (b) - (ii); (c) - (i) (a) - (i) ; (b) - (iii); (c) - (ii) (a) - (ii) ; (b) - (iii); (c) - (i)
1 vote
4
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
1 vote
5
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: $t(x,y) = 1-s(x,y)$ $t(x,y) = s(1-x,1-y)$ $t(x,y) = 1-s(1-x,1-y)$ $t(x,y) = s(1+x,1+y)$
1 vote
6
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
7
Which of the following is an example of unsupervised neural network? Back-propagation network Hebb network Associative memory network Self-organizing feature map
8
The value of the derivative of Sigmoid function given by $f(x)=\dfrac{1}{1+e^{-2x}}$ at $x=0$ is $0$ $\frac{1}{2}$ $\frac{1}{4}$ $\infty$
1 vote
9
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
10
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?
11
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
12
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
13
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? $h(n)=max\{h_1(n), \dots , h_m(n)\}$ $h(n)=min\{h_1(n), \dots , h_m(n)\}$ $h(n)=avg\{h_1(n), \dots , h_m(n)\}$ $h(n)=sum\{h_1(n), \dots , h_m(n)\}$
14
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
15
Which condition is used to influence a variable directly by all the others Partially Connected Full Connected Local Connected None of the above
16
Which agent enables the deliberation about the computational entities and actions ? Hybrid Reflective Relational None of the above
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
18
What is Artificial Intelligence ? Putting your intelligence into computer Programming with your own intelligence Making a machine intelligent Putting more memory into computer
1 vote
19
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
20
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
1 vote
21
Which formal system provides the semantic foundation for Prolog ? Predicate calculus Lambda calculus Hoare logic Propositional logic
1 vote
22
Criticism free idea generation is a factor of _____. Decision Support System Group Decision Support System Enterprise Resource Support System Artificial Intelligence
23
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.
24
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
25
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
26
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
27
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: $x_1-x_2-0.5=0$ $-x_1-x_2-0.5=0$ $0.5(x_1+x_2)-1.5=0$ $x_1+x_2-0.5=0$