(Test Bank) Artificial Intelligence MCQs

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This set of Artificial Intelligence Multiple Choice Questions & Answers (MCQs) focuses on “Robotics – 1”. 1. What is the name for information sent from robot sensors to robot controllers? a) temperature b) pressure c) feedback d) signal View Answer Answer: c Explanation: None. 2. Which of the following terms refers to the rotational motion of a robot arm? a) swivel b) axle c) retrograde d) roll View Answer Answer: d Explanation: None. 3. What is the name for space inside which a robot unit operates? a) environment b) spatial base c) work envelope d) exclusion zone View Answer Answer: c Explanation: None. 4. Which of the following terms IS NOT one of the five basic parts of a robot? a) peripheral tools b) end effectors c) controller d) drive View Answer Answer: a Explanation: None. 5. Decision support programs are designed to help managers make __________ a) budget projections b) visual presentations c) business decisions d) vacation schedules View AnswerAnswer: c Explanation: None. 6. PROLOG is an AI programming language which solves problems with a form of symbolic logic known as predicate calculus. It was developed in 1972 at the University of Marseilles by a team of specialists. Can you name the person who headed this team? a) Alain Colmerauer b) Niklaus Wirth c) Seymour Papert d) John McCarthy View Answer Answer: a Explanation: None. 7. The number of moveable joints in the base, the arm, and the end effectors of the robot determines_________ a) degrees of freedom b) payload capacity c) operational limits d) flexibility View Answer Answer: a Explanation: None. 8. Which of the following places would be LEAST likely to include operational robots? a) warehouse b) factory c) hospitals d) private homes View Answer Answer: d Explanation: None. 9. For a robot unit to be considered a functional industrial robot, typically, how many degrees of freedom would the robot have? a) three b) four c) six d) eight View Answer Answer: c Explanation: None. 10. Which of the basic parts of a robot unit would include the computer circuitry that could be programmed to determine what the robot would do?a) sensor b) controller c) arm d) end effector View Answer Answer: b This set of Artificial Intelligence Multiple Choice Questions & Answers (MCQs) focuses on “Image Perception”. 1. Which provides agents with information about the world they inhabit? a) Sense b) Perception c) Reading d) Hearing View Answer Answer: b Explanation: Perception provides agents with information about the world they inhabit. 2. What is used to initiate the perception in the environment? a) Sensor b) Read c) Actuators d) None of the mentioned View Answer Answer: a Explanation: A sensor is anything that can record some aspect of the environment. 3. What is the study of light? a) Biology b) Lightology c) Photometry d) All of the mentioned View Answer Answer: c Explanation: None. 4. How to increase the brightness of the pixel? a) Sound b) Amount of light c) Surface d) Waves View AnswerAnswer: b Explanation: The brightness of a pixel in the image is proportional to the amount of light directed towards the camera. 5. How many kinds of reflection are available in image perception? a) 1 b) 2 c) 3 d) 4 View Answer Answer: b Explanation: There are two kinds of reflection. They are the specular and diffuse reflection. 6. What is meant by predicting the value of a state variable from the past? a) Specular reflection b) Diffuse reflection c) Gaussian filter d) Smoothing View Answer Answer: d Explanation: Smoothing meant predicting the value of a state variable from the past and by given evidence and calculating the present and future. 7. How many types of image processing techniques are there in image perception? a) 1 b) 2 c) 3 d) 4 View Answer Answer: c Explanation: The three image processing techniques are smoothing, edge detection and image segmentation. 8. Which is meant by assuming any two neighboring that are both edge pixels with consistent orientation? a) Canny edge detection b) Smoothing c) Segmentation d) None of the mentioned View Answer Answer: a Explanation: Canny edge detection is assuming any two neighboring that are both edge pixels with consistent orientation and must belong to the same edge.9. What is the process of breaking an image into groups? a) Edge detection b) Smoothing c) Segmentation d) None of the mentioned View Answer Answer: c Explanation: Segmentation is the process of breaking an image into groups, based on the similarities of the pixels. 10. How many types of 3-D image processing techniques are there in image perception? a) 3 b) 4 c) 5 d) 6 View Answer Answer: c Explanation: The five types of 3-D image processing techniques are motion, binocular stereopsis, texture, shading and contour. This set of Artificial Intelligence Multiple Choice Questions & Answers (MCQs) focuses on “Speech Recognition”. 1. What is the dominant modality for communication between humans? a) Hear b) Speech c) Smell d) None of the mentioned View Answer Answer: b Explanation: Speech is the dominant modality for communication between humans and reliable speech recognition between machines. 2. What kind of signal is used in speech recognition? a) Electromagnetic signal b) Electric signal c) Acoustic signal d) Radar View Answer Answer: c Explanation: Acoustic signal is used to identify a sequence of words uttered by a speaker. 3. What is viewed as problem of probabilistic inference? a) Speech recognitionb) Speaking c) Hearing d) Utterance View Answer Answer: a Explanation: Speech recognition is viewed as problem of probabilistic inference because different words can sound the same. 4. Which specifies the prior probability of each utterance? a) Sound model b) Model c) Language model d) All of the mentioned View Answer Answer: c Explanation: Because it contains the group of words that can help to specify the prior probability of each utterance. 5. Which model gives the probability of each word following each other word? a) Bigram model b) Diagram model c) Gram model d) Speech model View Answer Answer: a Explanation: Bigram model gives the probability of each word following each other word in speech recognition. 6. What is the study of how the language sounds? a) Speechology b) Biology c) Trilogy d) Phonology View Answer Answer: d Explanation: None. 7. What are periodic changes in pressure that propagate through the air? a) Air waves b) Sound waves c) Rate d) None of the mentioned View Answer Answer: b Explanation: Sound waves are periodic changes in pressure that propagate through the air and it can be measured by a microphone.8. What is called as the properties of the signal that extend over interval? a) Hops b) Rate c) Frames d) All of the mentioned View Answer Answer: c Explanation: Speech system summarize the properties of the signal that extend over interval called frames. 9. Which is used to capture the internal structure of the phones? a) One-state phone model b) Two-state phone model c) Three-state phone mone d) All of the mentioned View Answer Answer: c Explanation: None. 10. Which are partially captured by triphone model? a) Articulation effects b) Coarticulation effects c) Both Articulation & Coarticulation effects d) None of the mentioned View Answer Answer: b Explanation: Coarticulation effects are partially captured by triphone model, which can be manipulated by acoustic model. This set of Artificial Intelligence Multiple Choice Questions & Answers (MCQs) focuses on “Perception”. 1. The process by which you become aware of messages through your sense is called ____________ a) Organization b) Sensation c) Interpretation-Evaluation d) Perception View Answer Answer: d Explanation: None. 2. Susan is so beautiful; I bet she is smart too. This is an example of __________ a) The halo effect b) The primary effect c) A self-fulfilling prophecyd) The recency effect View Answer Answer: a Explanation: None. 3. _____ prevents you from seeing an individual as an individual rather than as a member of a group. a) Cultural mores b) Stereotypes c) Schematas d) Attributions View Answer Answer: c Explanation: None. 4. When you get fired from your job and you determine it is because your boss dislikes you, you are most likely exhibiting? a) Self-promotion b) Fundamental attribution error c) Over-attribution d) Self-serving bias View Answer Answer: d Explanation: None. 5. What is Mindless processing? a) careful, critical thinking b) inaccurate and faulty processing c) information processing that relies heavily on familiar schemata d) processing that focuses on unusual or novel events View Answer Answer: c Explanation: None. 6. Selective retention occurs when? a) we process, store, and retrieve information that we have already selected, organized, and interpreted b) we make choices to experience particular stimuli c) we make choices to avoid particular stimuli d) we focus on specific stimuli while ignoring other stimuli View Answer Answer: a Explanation: None. 7. Which of the following strategies would NOT be effective at improving your communication competence?a) Recognize the people, objects, and situations remain stable over time b) Recognize that each person’s frame of perception is unique c) Be active in perceiving d) Distinguish facts from inference View Answer Answer: a Explanation: None. 8. _____________ is measured by the number of mental structures we use, how abstract they are, and how elaborate they interact to shape our perceptions. a) intrapersonal structure b) perceptual set c) self-justification d) none of the mentioned View Answer Answer: d Explanation: None. 9. What is a perception check? a) a cognitive bias that makes us listen only to information we already agree with b) a method teachers use to reward good listeners in the classroom c) any factor that gets in the way of good listening and decreases our ability to interpret correctly d) a response that allows you to state your interpretation and ask your partner whether or not that interpretation is correct View Answer Answer: d Explanation: None. This set of Artificial Intelligence Multiple Choice Questions & Answers (MCQs) focuses on “Communication”. 1. What is the intentional exchange of information brought about by production and perception? a) Hearing b) Communication c) Speech d) None of the mentioned View Answer Answer: b Explanation: Communication is the intentional exchange of information brought about by the production and perception of signs drawn from a shared system. 2. What is the complex system of structured message? a) Languages b) Wordsc) Signs d) Speech View Answer Answer: a Explanation: Language is the complex system of structured message that enables us to communicate. 3. How many things are present in conventional communication signs? a) 3 b) 4 c) 5 d) 6 View Answer Answer: c Explanation: The five things present in the conventional communication system are query, inform, request, acknowledge and promise. 4. What is defined by a set of strings? a) Signs b) Formal language c) Communication d) None of the mentioned View Answer Answer: b Explanation: A formal language is defined by a set of strings that is a concatenation of terminal symbols. 5. What is a finite set of rules that specifies a language? a) Signs b) Communication c) Grammar d) Phrase View Answer Answer: c Explanation: None. 6. What kind of perception is used in printing? a) Optical character recognition b) Speech recognition c) Perception d) None of the mentioned View Answer Answer: a Explanation: When perception is used in printing means, It is called as optical character recognition.7. Why the parsing is used? a) Interpretation b) Building a parse tree c) Recognition d) All of the mentioned View Answer Answer: b Explanation: Parsing is the process of building a parse tree for an input string. 8. How many objects are available in closed classes? a) 1 b) 2 c) 3 d) 4 View Answer Answer: d Explanation: The four objects are available in closed classes are pronoun, article, preposition and conjunction. 9. How many states are present in parsing? a) 1 b) 2 c) 3 d) 4 View Answer Answer: c Explanation: The three state available in parsing are initial state, successor function and goal test. 10. Pick out the correct option about the types of parsing. a) Top-down and bottom-up parsing b) Interpretation and communication c) Roll-up and roll-down d) None of the mentioned View Answer Answer: a Explanation: The two types of parsing are top-down parsing and bottom-up parsing. 11. Semantic grammars are _____________ a) Encode semantic information into a syntactic grammar b) Decode semantic information into a syntactic grammar c) Encode syntactic information into a semantic grammar d) Decode syntactic information into a semantic grammar View AnswerAnswer: a Explanation: Semantic grammars encode semantic information into a syntactic grammar. 12. What is a top-down parser? a) Begins by hypothesizing a sentence (the symbol S) and successively predicting lower level constituents until individual pre-terminal symbols are written b) Begins by hypothesizing a sentence (the symbol S) and successively predicting upper level constituents until individual pre-terminal symbols are written c) Begins by hypothesizing lower level constituents and successively predicting a sentence (the symbol S) d) Begins by hypothesizing upper level constituents and successively predicting a sentence (the symbol S) View Answer Answer: a Explanation: A top-down parser begins by hypothesizing a sentence (the symbol S) and successively predicting lower level constituents until individual pre-terminal symbols are written. 13. Perception involves __________ a) Sights, sounds, smell and touch b) Hitting c) Boxing d) Dancing View Answer Answer: a Explanation: Perception involves Sights, sounds, smell and touch. This set of Artificial Intelligence Multiple Choice Questions & Answers (MCQs) focuses on “Inductive logic programming”. 1. Which combines inductive methods with the power of first-order representations? a) Inductive programming b) Logic programming c) Inductive logic programming d) Lisp programming View Answer Answer: c Explanation: Inductive logic programming(ILP) combines inductive methods with the power of first-order representations. 2. How many reasons are available for the popularity of ILP? a) 1 b) 2 c) 3d) 4 View Answer Answer: c Explanation: The three reasons available for the popularity of ILP are general knowledge, Complete algorithm and hypotheses. 3. Which cannot be represented by a set of attributes? a) Program b) Three-dimensional configuration of a protein molecule c) Agents d) None of the mentioned View Answer Answer: b Explanation: Because the configuration inherently refers to relationships between objects. 4. Which is an appropriate language for describing the relationships? a) First-order logic b) Propositional logic c) ILP d) None of the mentioned View Answer Answer: a Explanation: None. 5. Which produces hypotheses that are easy to read for humans? a) ILP b) Artificial intelligence c) Propositional logic d) First-order logic View Answer Answer: a Explanation: Because ILP can participate in the scientific cycle of experimentation, So that it can produce flexible structure. 6. What need to be satisfied in inductive logic programming? a) Constraint b) Entailment constraint c) Both Constraint & Entailment constraint d) None of the mentioned View Answer Answer: b Explanation: The objective of an ILP is to come up with a set of sentences for the hypothesis such that the entailment constraint is satisfied.7. How many literals are available in top-down inductive learning methods? a) 1 b) 2 c) 3 d) 4 View Answer Answer: c Explanation: The three literals are available in top-down inductive learning methods are predicates, equality and inequality and arithmetic literals. 8. Which inverts a complete resolution strategy? a) Inverse resolution b) Resolution c) Trilogy d) None of the mentioned View Answer Answer: a Explanation: Because it is a complete algorithm for learning first-order theories. 9. Which method can’t be used for expressing relational knowledge? a) Literal system b) Variable-based system c) Attribute-based system d) None of the mentioned View Answer Answer: c Explanation: ILP methods can learn relational knowledge that is not expressible in attribute-based system. 10. Which approach is used for refining a very general rule through ILP? a) Top-down approach b) Bottom-up approach c) Both Top-down & Bottom-up approach d) None of the mentioned View Answer Answer: a Explanation: None. This set of Artificial Intelligence Multiple Choice Questions & Answers (MCQs) focuses on “Decision Trees”. 1. A _________ is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. a) Decision tree b) Graphsc) Trees d) Neural Networks View Answer Answer: a Explanation: Refer the definition of Decision tree. 2. Decision Tree is a display of an algorithm. a) True b) False View Answer Answer: a Explanation: None. 3. What is Decision Tree? a) Flow-Chart b) Structure in which internal node represents test on an attribute, each branch represents outcome of test and each leaf node represents class label c) Flow-Chart & Structure in which internal node represents test on an attribute, each branch represents outcome of test and each leaf node represents class label d) None of the mentioned View Answer Answer: c Explanation: Refer the definition of Decision tree. 4. Decision Trees can be used for Classification Tasks. a) True b) False View Answer Answer: a Explanation: None. 5. Choose from the following that are Decision Tree nodes? a) Decision Nodes b) End Nodes c) Chance Nodes d) All of the mentioned View Answer Answer: d Explanation: None. 6. Decision Nodes are represented by ____________ a) Disks b) Squares c) Circles d) Triangles View AnswerAnswer: b Explanation: None. 7. Chance Nodes are represented by __________ a) Disks b) Squares c) Circles d) Triangles View Answer Answer: c Explanation: None. 8. End Nodes are represented by __________ a) Disks b) Squares c) Circles d) Triangles View Answer Answer: d Explanation: None. 9. Which of the following are the advantage/s of Decision Trees? a) Possible Scenarios can be added b) Use a white box model, If given result is provided by a model c) Worst, best and expected values can be determined for different scenarios d) All of the mentioned View Answer Answer: d Explanation: None. This set of Artificial Intelligence Multiple Choice Questions & Answers (MCQs) focuses on “Decision Trees”. 1. A _________ is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. a) Decision tree b) Graphs c) Trees d) Neural Networks View Answer Answer: a Explanation: Refer the definition of Decision tree. 2. Decision Tree is a display of an algorithm. a) Trueb) False View Answer Answer: a Explanation: None. 3. What is Decision Tree? a) Flow-Chart b) Structure in which internal node represents test on an attribute, each branch represents outcome of test and each leaf node represents class label c) Flow-Chart & Structure in which internal node represents test on an attribute, each branch represents outcome of test and each leaf node represents class label d) None of the mentioned View Answer Answer: c Explanation: Refer the definition of Decision tree. 4. Decision Trees can be used for Classification Tasks. a) True b) False View Answer Answer: a Explanation: None. 5. Choose from the following that are Decision Tree nodes? a) Decision Nodes b) End Nodes c) Chance Nodes d) All of the mentioned View Answer Answer: d Explanation: None. 6. Decision Nodes are represented by ____________ a) Disks b) Squares c) Circles d) Triangles View Answer Answer: b Explanation: None. 7. Chance Nodes are represented by __________ a) Disks b) Squares c) Circlesd) Triangles View Answer Answer: c Explanation: None. 8. End Nodes are represented by __________ a) Disks b) Squares c) Circles d) Triangles View Answer Answer: d Explanation: None. 9. Which of the following are the advantage/s of Decision Trees? a) Possible Scenarios can be added b) Use a white box model, If given result is provided by a model c) Worst, best and expected values can be determined for different scenarios d) All of the mentioned View Answer Answer: d Explanation: None. This set of AI Multiple Choice Questions & Answers 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. View Answer Answer: d Explanation: None. 2. 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 View AnswerAnswer: c Explanation: Back propagation is the transmission of error back through the network to allow weights to be adjusted so that the network can learn. 3. 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 View Answer Answer: b Explanation: Linearly separable problems of interest of neural network researchers because they are the only class of problem that Perceptron can solve successfully. 4. Which of the following is not the promise of artificial neural network? a) It can explain result b) It can survive the failure of some nodes c) It has inherent parallelism d) It can handle noise View Answer Answer: a Explanation: The artificial Neural Network (ANN) cannot explain result. 5. Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions View Answer Answer: a Explanation: Neural networks are complex linear functions with many parameters. 6. 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 View Answer Answer: a Explanation: Yes the perceptron works like that. 7. 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 functionb) Heaviside function c) Logistic function d) Perceptron function View Answer Answer: b Explanation: Also known as the step function – so answer 1 is also right. It is a hard thresholding function, either on or off with no in-between. 8. 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 View Answer Answer: c Explanation: None. 9. 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 View Answer Answer: c Explanation: RNN (Recurrent neural network) topology involves backward links from output to the input and hidden layers. 10. Which of the following is an application of NN (Neural Network)? a) Sales forecasting b) Data validation c) Risk management d) All of the mentioned View Answer Answer: d Explanation: All mentioned options are applications of Neural Network. This set of Artificial Intelligence Multiple Choice Questions & Answers (MCQs) focuses on “Neural Networks – 1”.1. A 3-input neuron is trained to output a zero when the input is 110 and a one when the input is 111. After generalization, the output will be zero when and only when the input is? a) 000 or 110 or 011 or 101 b) 010 or 100 or 110 or 101 c) 000 or 010 or 110 or 100 d) 100 or 111 or 101 or 001 View Answer Answer: c Explanation: The truth table before generalization is: InputsOutput 000$ 001$ 010$ 011$ 100$ 101$ 1100 1111 where $ represents don’t know cases and the output is random. After generalization, the truth table becomes: InputsOutput 0000 0011 0100 0111 1000 1011 11001111 2. 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 View Answer Answer: a Explanation: The perceptron is a single layer feed-forward neural network. It is not an auto-associative network because it has no feedback and is not a multiple layer neural network because the pre-processing stage is not made of neurons. 3. What is an auto-associative network? a) a neural network that contains no loops b) a neural network that contains feedback c) a neural network that has only one loop d) a single layer feed-forward neural network with pre-processing View Answer Answer: b Explanation: An auto-associative network is equivalent to a neural network that contains feedback. The number of feedback paths(loops) does not have to be one. 4. A 4-input neuron has weights 1, 2, 3 and 4. The transfer function is linear with the constant of proportionality being equal to 2. The inputs are 4, 10, 5 and 20 respectively. What will be the output? a) 238 b) 76 c) 119 d) 123 View Answer Answer: a Explanation: The output is found by multiplying the weights with their respective inputs, summing the results and multiplying with the transfer function. Therefore: Output = 2 * (1*4 + 2*10 + 3*5 + 4*20) = 238. 5. Which of the following is true? (i) On average, neural networks have higher computational rates than conventional computers. (ii) Neural networks learn by example. (iii) Neural networks mimic the way the human brain works. a) All of the mentioned are true b) (ii) and (iii) are true c) (i), (ii) and (iii) are true d) None of the mentioned View AnswerAnswer: a Explanation: Neural networks have higher computational rates than conventional computers because a lot of the operation is done in parallel. That is not the case when the neural network is simulated on a computer. The idea behind neural nets is based on the way the human brain works. Neural nets cannot be programmed, they can only learn by examples. 6. Which of the following is true for neural networks? (i) The training time depends on the size of the network. (ii) Neural networks can be simulated on a conventional computer. (iii) Artificial neurons are identical in operation to biological ones. a) All of the mentioned b) (ii) is true c) (i) and (ii) are true d) None of the mentioned View Answer Answer: c Explanation: The training time depends on the size of the network; the number of neuron is greater and therefore the number of possible ‘states’ is increased. Neural networks can be simulated on a conventional computer but the main advantage of neural networks – parallel execution – is lost. Artificial neurons are not identical in operation to the biological ones. 7. What are the advantages of neural networks over conventional computers? (i) They have the ability to learn by example (ii) They are more fault tolerant (iii)They are more suited for real time operation due to their high ‘computational’ rates a) (i) and (ii) are true b) (i) and (iii) are true c) Only (i) d) All of the mentioned View Answer Answer: d Explanation: Neural networks learn by example. They are more fault tolerant because they are always able to respond and small changes in input do not normally cause a change in output. Because of their parallel architecture, high computational rates are achieved. 8. Which of the following is true? Single layer associative neural networks do not have the ability to: (i) perform pattern recognition (ii) find the parity of a picture (iii)determine whether two or more shapes in a picture are connected or not a) (ii) and (iii) are trueb) (ii) is true c) All of the mentioned d) None of the mentioned View Answer Answer: a Explanation: Pattern recognition is what single layer neural networks are best at but they don’t have the ability to find the parity of a picture or to determine whether two shapes are connected or not. 9. Which is true for neural networks? a) It has set of nodes and connections b) Each node computes it’s weighted input c) Node could be in excited state or non-excited state d) All of the mentioned View Answer Answer: d Explanation: All mentioned are the characteristics of neural network. 10. What is Neuro software? a) A software used to analyze neurons b) It is powerful and easy neural network c) Designed to aid experts in real world d) It is software used by Neurosurgeon View Answer Answer: b Explanation: None. This set of Artificial Intelligence online test focuses on “Learning – 3”. 1. Which is not a desirable property of a logical rule-based system? a) Locality b) Attachment c) Detachment d) Truth-Functionality View Answer Answer: b Explanation: Locality: In logical systems, whenever we have a rule of the form A => B, we can conclude B, given evidence A, without worrying about any other rules. Detachment: Once a logical proof is found for a proposition B, the proposition can be used regardless of how it was derived .That is, it can be detachment from its justification. Truth-functionality: In logic, the truth of complex sentences can be computed from the truth of the components. However, there are no Attachment properties lies in a Rule-based system. Global attribute defines a particular problem space as user specific and changes according to user’s plan to problem.2. How is Fuzzy Logic different from conventional control methods? a) IF and THEN Approach b) FOR Approach c) WHILE Approach d) DO Approach View Answer Answer: a Explanation: FL incorporates a simple, rule-based IF X AND Y THEN Z approach to a solving control problem rather than attempting to model a system mathematically. 3. In an Unsupervised learning ____________ a) Specific output values are given b) Specific output values are not given c) No specific Inputs are given d) Both inputs and outputs are given View Answer Answer: b Explanation: The problem of unsupervised learning involves learning patterns in the input when no specific output values are supplied. We cannot expect the specific output to test your result. Here the agent does not know what to do, as he is not aware of the fact what propose system will come out. We can say an ambiguous un- proposed situation. 4. Inductive learning involves finding a __________ a) Consistent Hypothesis b) Inconsistent Hypothesis c) Regular Hypothesis d) Irregular Hypothesis View Answer Answer: a Explanation: Inductive learning involves finding a consistent hypothesis that agrees with examples. The difficulty of the task depends on the chosen representation. 5. Computational learning theory analyzes the sample complexity and computational complexity of __________ a) Unsupervised Learning b) Inductive learning c) Forced based learning d) Weak learning View Answer Answer: b Explanation: Computational learning theory analyzes the sample complexity and computational complexity of inductive learning. There is a tradeoff between the expressiveness of the hypothesis language and the ease of learning.