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

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
by

1 Answer

Answer :

c) True – perceptrons can do this but are unable to learn to do it – they have to be  explicitly hand-coded
by

Related questions

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.

Description : 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 ... solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Last Answer : d) Because it is the simplest linearly inseparable problem that exists.

This set of Artificial Intelligence MCQs focuses on “Neural Networks – 2”. 1. 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.

Description : This set of Artificial Intelligence MCQs focuses on Neural Networks - 2 . 1. Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in ... by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Last Answer : d) Because it is the simplest linearly inseparable problem that exists.

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

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Last Answer : b) Because they are the only class of problem that Perceptron can solve successfully

The network that involves backward links from output to the input and hidden layers is called _________ a) Self organizing maps b) Perceptrons c) Recurrent neural network d) Multi layered perceptron

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Last Answer : c) Recurrent neural network

The problem-solving agent with several immediate options of unknown value can decide what to do by just examining different possible sequences of actions that lead to states of known value, and then choosing the best sequence. This process of looking for such a sequence is called Search. a) True b) False

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Last Answer : a) True

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

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Consider a single perception with weights as given in the following figure: The above perception can solve (A) OR problem (B) AND problem (C) XOR problem (D) All of the above

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Last Answer : (B) AND problem

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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

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Last Answer : c) It is the transmission of error back through the network to allow weights to be adjusted so that the network can learn

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

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Last Answer : c) It is the transmission of error back through the network to allow weights to be adjusted so that the network can learn.

What can be viewed as a single lateral of disjunction? a) Multiple clause b) Combine clause c) Unit clause d) None of the mentioned

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Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

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Last Answer : a) Linear Functions

Neural Networks are complex ______________with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

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Last Answer : b) Nonlinear Functions

Neural Networks are complex ———————–with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions e) Power Functions

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Last Answer : b) Nonlinear Functions

Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

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What is perceptron? 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

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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

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Perceptron is A. General class of approaches to a problem. B. Performing several computations simultaneously C. Structures in a database those are statistically relevant D. Simple forerunner of modern neural networks, without hidden layers

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What is the major component/components for measuring the performance of problem solving? a) Completeness b) Optimality c) Time and Space complexity d) All of the mentioned

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ANN is composed of large number of highly interconnected processing elements(neurons) working in unison to solve problems. A. True B. False C. D.

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What is the name of the function in the following statement “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) Step function b) Heaviside function c) Logistic function d) Perceptron function

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Planning graphs works only for prepositional planning problems. a) True b) False

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The Hungarian method for solving an assignment problem can also be used to solve: a. A transportation problem b. A travelling salesman problem c. A linear programming problem d. Both a and b

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Three gods, A, B, and C, are called, in some order, True, False, and Random. True always speaks truly, False always speaks falsely, but whether Random speaks truly or falsely is completely random. You must determine the identities of A, B, and C by asking three yes-or-no questions, and each question must be posed to exactly one god. The gods understand English, but will answer all questions in their own language. In their unknown language, the words for 'yes' and 'no' are 'da' and 'ja', in some order. You do not know which word means which. So, which questions would you ask to identify each god? And no, it’s not a trick question. As a matter of fact, there are multiple ways to get the correct answer. -Riddles

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What is the term used for describing the judgmental or commonsense part of problem solving? a) Heuristic b) Critical c) Value based d) Analytical

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Which term is used for describing the judgmental or commonsense part of problem solving? a) Heuristic b) Critical c) Value based d) Analytical

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What is the term used for describing the judgmental or commonsense part of problem solving? A. Heuristic B. Critical C. Value based D. Analytical

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What is the term used for describing the judgmental or commonsense part of problem solving? A. Heuristic B. Critical C. Value based D. Analytical E. None of the above

Description : What is the term used for describing the judgmental or commonsense part of problem solving? A. Heuristic B. Critical C. Value based D. Analytical E. None of the above

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A knowledge-based agent can combine general knowledge with current percepts to infer hidden aspects of the current state prior to selecting actions. a) True b) False

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Homozygous refers to: a) similar types of chromosomes b) having similar functions on an evolutionary basis c) particles in solution that are inseparable d) having identical alleles for a given gene

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A problem solver is a style of problem solving reflected by the manager (a) Who confronts the problem, reacts to it, and makes those changes necessary solve it. (b) Who notices a problem and does not react. (c) Who actively looks at situations, searching for problems or anticipating possible problems so that corrective action can be taken before the problem grows. ; (d) None of the above

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A perceptron is a ______________ a) Feed-forward neural network b) Backpropagation algorithm c) Backtracking algorithm d) Feed Forward-backward algorithm

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Vygotsky theory implies Options: A) child will learn best in the company of children having IQ lesser than his/her own. B) collaborative problem solving C) individual assignments to each student D) after initial explanation, do not support a child in solving difficult questions

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