# Artificial Intelligence And Soft Computing MCQ - QPkendra

Question 31 : which of the following is Derivative Based Optimization method?

1. Newton's Method
2. Simulated Annealing.
3. Genetic Algorithm
4. Downhill simplex search

Question 32 : Which of the following is the correct definition of “an aunt” in FOL? Here, Aunt(x,y) is read as x is an aunt of y and Sister(x,y) is read as x is a sister of y.

1. ∀x ∀y (Aunt(x,y) ---> ∀z (Sister(z, x) v Parent(z, y)))
2. ∀x ∀y (Aunt(x,y) ---> ∃z (Sister(z,x) ∧ Parent(z,y)))
3. ∀x ∀y (Aunt(x,y) ---> ∃z (Sister(x,z) ∧ Parent(z,y)))
4. ∀x ∀y (Aunt(x,y) ---> ∃z (Sister(x,z) ---> Parent(z,y)))

Question 33 : It converts the fuzzy quantities into crisp quantities.

1. Knowledge base
2. defuzzification unit
3. fuzzification unit
4. Decision-making Unit

Question 34 : which of the following is slower optimization method?

1. Simulated Annealing.
2. Genetic Algorithm
3. random search
4. steepest descent

Question 35 : During learning, if a Perceptron misclassifies a training data positively, i.e., erroneously yields an output +1 instead of –1, the interconnection weights are ..............

1. Increased
2. Decreased
3. Kept unaltered
4. make it zero

Question 36 : ____________________ is tolerant to imprecision and uncertainty and follows a multivalued logic.

1. Hard Computing
2. Soft Computing
3. Analytical Model based computing

Question 37 : What is back propagation?

1. It is another name given to the curvy function in the perceptron
2. It is the transmission of error back through the network to adjust the inputs
3. It is the transmission of error back through the network to allow weights to be adjusted so that the network can learn
4. to develop learning algorithm for single layer feedforward neural network

Question 38 : Choose the correct option for soft computing technique

1. Soft computing is deterministic
2. Soft computing output is precise
3. Soft computing is based on crisp logic
4. Soft computing can deal with incomplete, uncertain and noisy data.

Question 39 : What is TRUE for linear activation functions.

1. Weights and biases of neural network with linear activation function will not get updated during backpropogation.
2. The network with linear activation function will not be able to learn complex patterns in data.
3. They can be used only for binary classifier
4. The derivative of linear activation function is zero.

Question 40 : _________________explores the parameter space of an objective function sequentially in a seemingly random fashion to find the optimal point that minimizes or maximizes the objective function.

1. Random search
2. Simulated Annealing.
3. Newton's Method
4. steepest descent

Question 41 : In Membership function graph x-axis represents?

1. Universe of discourse
2. degrees of membership in the [0, 1] interval
3. degrees of discourse
4. Universe of membership

Question 42 : Which approach is most suited to structured problems with little uncertainty

1. Simulation
2. human intuition
3. Optimization
4. genetic algorithms

Question 43 : Fuzzy logic is useful for both commercial and practical purposes.

1. True, False.
2. True, True
3. False, False
4. False, True

Question 44 : Which environment is called as semi dynamic?

1. Environment does not change with the passage of time
2. Agent performance changes
3. Environment will be changed
4. Agent performance does not change

Question 45 : In the case of______________, both artificial neural network and fuzzy system work independently from each other.

1. cooperative neural fuzzy systems
2. Artificial Neural Network
3. Neural Network
4. neuro fuzzy system

Question 46 : Suppose you are designing a handwritten digit recognition system using MLP.Dataset contains 28*28 pixel images of handwritten digits from 0-9.Choose the correct number of neuron for input and output layer.

1. Input layer:100 neurons and Output layer:9 neuron.
2. Input layer:100 neurons and Output layer:100 neuron
3. Input layer:10 neurons and Output layer:2 neuron
4. Input layer:784 neurons and Output layer:10 neuron

Question 47 : Any soft‐computing methodology is characterized with

1. precise solutions
2. control actions are unambiguous and accurate
3. Control action is formally defined
4. algorithm which can easily adapt with the change of dynamic environment

Question 48 : Classification and Regression are the examples of ............learning

1. Supervised
2. Unsupervised
3. dependent
4. Specialized

Question 49 : Rules are expressed as a set of?

1. Switch statement
2. Using Loop
3. if-then statements
4. Using continue statement

Question 50 : Genetic algorithms belong to the family of methods in the

1. artificial intelligence area
2. optimization area
3. complete enumeration family of methods
4. Non-computer based (human) solutions area

Question 51 : Based on thougth/learning , behaviour and performance which is not the concept involved in AI definition?

1. Think Humanly
2. Think Rationally
3. Act Humanly
4. Act Mechanically

Question 52 : ____ is not a Critical category of AI, based on the capacity of intelligence.

1. Atificial Moderate Intelligence
2. Atificial Narrow Intelligence
3. AtificialGeneral Intelligence
4. AtificialSuper Intelligence

Question 53 : ___agent doesn’t maintain an internal state that depends on the percept history.

1. Simpe Reflex Agent
2. Utility Based Agent
3. Goal Based Agent
4. Model Based Agent

Question 54 : The suitable task environment for Fighter plane simulator agent is___

1. Fully Observable
2. Deterministic
3. Dynamic
4. Episodic

Question 55 : ____Agent provides crude binary distinction between Happy and Unhappy states

1. Simple reflex agent
2. Model based agent
3. Learning agent
4. Goal Based agent

Question 56 : For a perfect binary tree if BFS visits the nodes in following order : A,B,C,D,E,F,G then what will be order for DFS ?

1. A,B,C,D,,E,F,G
2. A,B,D,C,F,G,E,
3. A,B,D,E,C,F,G
4. A,B,D,E,E,G,F

Question 57 : ___ can not be admissible Hueristic for 8 puzzle problem.

1. Number of tiles in place
2. Number of misplaced tiles
3. Manhattan Distance
4. Manchester Distance

Question 58 : For a perfect binary tree if BFS visits the nodes in following order : A,B,C,D,E,F,G then what will be order for Iterative deepening DFS ?

1. A,B,C,D,,E,F,G
2. A,B,D,C,F,G,E,
3. A,B,D,E,C,F,G
4. A,B,D,E,E,G,F

Question 59 : Number of Nodes expanded in MinMax algorithm is _____ that of Alpha Beta Pruning method.

1. less than
2. always same as
3. same or greater than
4. less or same as

Question 60 : Local beam search with k = 1 is _____ search

1. Depth First
2. Iterative deepening
3. Hill Climbing