78 + Interview Questions in Uncertain Knowledge And Reasoning in Artificial Intelligence Page 1 InterviewSolution

1.	Which of the following applications include in the Strategic Computing Program?(a) battle management(b) autonomous systems(c) pilot’s associate(d) all of the mentionedI had been asked this question during an interview.This is a very interesting question from Expert Systems topic in division Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» CORRECT OPTION is (d) all of the mentioned The BEST EXPLANATION: NONE.

Discussion

2.	Input segments of AI programming contain(s)?(a) sound(b) smell(c) touch(d) none of the mentionedI got this question in an interview for internship.Asked question is from Expert Systems in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The CORRECT CHOICE is (d) NONE of the mentioned For EXPLANATION: None.

Discussion

3.	In his landmark book Cybernetics, Norbert Wiener suggested a way of modeling scientific phenomena using not energy, but ___________(a) mathematics(b) intelligence(c) information(d) historyThe question was asked in an international level competition.My question comes from Expert Systems topic in section Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The CORRECT ANSWER is (c) information To explain I WOULD SAY: None.

Discussion

4.	The first widely-used commercial form of Artificial Intelligence (Al) is being used in many popular products like microwave ovens, automobiles and plug in circuit boards for desktop PCs. It allows machines to handle vague information with a deftness that mimics human intuition. What is the name of this Artificial Intelligence?(a) Boolean logic(b) Human logic(c) Fuzzy logic(d) Functional logicI have been asked this question in a national level competition.This question is from Expert Systems topic in portion Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The CORRECT ANSWER is (C) Fuzzy logic The explanation is: NONE.

Discussion

5.	MCC is investigating the improvement of the relationship between people and computers through a technology called ___________(a) computer-aided design(b) human factors(c) parallel processing(d) all of the mentionedI had been asked this question in an interview for internship.I want to ask this question from Expert Systems in division Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The correct choice is (B) HUMAN factors The EXPLANATION: None.

Discussion

6.	The “Turing Machine” showed that you could use a/an _____ system to program any algorithmic task.(a) binary(b) electro-chemical(c) recursive(d) semanticThe question was asked in an interview.I'm obligated to ask this question of Expert Systems topic in division Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The CORRECT ANSWER is (a) binary Best EXPLANATION: NONE.

Discussion

7.	An AI system developed by Daniel Bobrow to read and solve algebra word problems.(a) SHRDLU(b) SIMD(c) BACON(d) STUDENTI got this question at a job interview.I'm obligated to ask this question of Expert Systems topic in section Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» CORRECT OPTION is (d) STUDENT The EXPLANATION: NONE.

Discussion

8.	Which of the following is an advantage of using an expert system development tool?(a) imposed structure(b) knowledge engineering assistance(c) rapid prototyping(d) all of the mentionedThis question was posed to me by my college professor while I was bunking the class.This question is from Expert Systems in division Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» CORRECT OPTION is (d) all of the mentioned Easiest EXPLANATION: NONE.

Discussion

9.	In LISP, the function returns t if is even and nil otherwise ___________(a) (evenp )(b) (even )(c) (numeven )(d) (numnevenp )I have been asked this question in my homework.This intriguing question originated from Expert Systems topic in section Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» CORRECT OPTION is (a) (evenp ) For explanation I WOULD say: None.

Discussion

10.	Which suggests the existence of an efficient recursive algorithm for online smoothing?(a) Matrix(b) Constant space(c) Constant time(d) None of the mentionedI have been asked this question in quiz.My question comes from Hidden Markov Model topic in portion Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Correct ANSWER is (b) CONSTANT space To ELABORATE: NONE.

Discussion

11.	Which reveals an improvement in online smoothing?(a) Matrix formulation(b) Revelation(c) HMM(d) None of the mentionedI got this question in a national level competition.Question is taken from Hidden Markov Model in portion Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The correct choice is (a) Matrix formulation To EXPLAIN: Matrix formulation REVEALS an IMPROVEMENT in online smoothing with a FIXED LAG.

Discussion

12.	Which algorithm works by first running the standard forward pass to compute?(a) Smoothing(b) Modified smoothing(c) HMM(d) Depth-first search algorithmThis question was addressed to me at a job interview.My question is based upon Hidden Markov Model topic in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Right CHOICE is (b) MODIFIED SMOOTHING Easiest explanation: The modified smoothing algorithm works by first running the standard FORWARD PASS to compute and then running the backward pass.

Discussion

13.	Which variable can give the concrete form to the representation of the transition model?(a) Single variable(b) Discrete state variable(c) Random variable(d) Both Single & Discrete state variableThe question was posed to me in an interview.This intriguing question comes from Hidden Markov Model in division Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The correct choice is (d) Both SINGLE & DISCRETE state variable The best explanation: With a single, discrete state variable, we can GIVE concrete form to the representation of the TRANSITION model.

Discussion

14.	Where does the Hidden Markov Model is used?(a) Speech recognition(b) Understanding of real world(c) Both Speech recognition & Understanding of real world(d) None of the mentionedI had been asked this question in an interview for job.My question is from Hidden Markov Model in portion Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» RIGHT OPTION is (a) SPEECH recognition Best EXPLANATION: NONE.

Discussion

15.	Which allows for a simple and matrix implementation of all the basic algorithm?(a) HMM(b) Restricted structure of HMM(c) Temporary model(d) Reality modelThis question was addressed to me in an online quiz.Question is taken from Hidden Markov Model topic in section Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The CORRECT option is (B) RESTRICTED STRUCTURE of HMM Explanation: Restricted structure of HMM allows for a very simple and elegant matrix implementation of all the basic ALGORITHM.

Discussion

16.	Where does the additional variables are added in HMM?(a) Temporal model(b) Reality model(c) Probability model(d) All of the mentionedI got this question by my college director while I was bunking the class.This is a very interesting question from Hidden Markov Model topic in section Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Correct choice is (a) Temporal model For EXPLANATION: Additional state VARIABLES can be ADDED to a temporal model while staying WITHIN the HMM framework.

Discussion

17.	How does the state of the process is described in HMM?(a) Literal(b) Single random variable(c) Single discrete random variable(d) None of the mentionedI have been asked this question in an interview for job.This intriguing question originated from Hidden Markov Model in portion Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Right choice is (c) Single discrete random variable The BEST explanation: An HMM is a temporal probabilistic model in which the state of the PROCESS is DESCRIBED by a single discrete random variable.

Discussion

18.	What are the possible values of the variable?(a) Variables(b) Literals(c) Discrete variable(d) Possible states of the worldThe question was asked in an interview for internship.I'm obligated to ask this question of Hidden Markov Model topic in section Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The CORRECT choice is (d) Possible states of the WORLD The explanation: The possible VALUES of the variables are the possible states of the world.

Discussion

19.	Which algorithm is used for solving temporal probabilistic reasoning?(a) Hill-climbing search(b) Hidden markov model(c) Depth-first search(d) Breadth-first searchThis question was addressed to me in semester exam.This intriguing question originated from Hidden Markov Model topic in division Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The correct option is (b) Hidden MARKOV model The best explanation: Hidden Markov model is USED for solving temporal probabilistic REASONING that was independent of TRANSITION and SENSOR model.

Discussion

20.	______________ is/are the way/s to represent uncertainty.(a) Fuzzy Logic(b) Probability(c) Entropy(d) All of the mentionedThis question was addressed to me in an online interview.My question comes from Fuzzy Logic in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Correct ANSWER is (d) All of the mentioned To elaborate: ENTROPY is amount of UNCERTAINTY INVOLVED in DATA. Represented by H(data).

Discussion

21.	Like relational databases there does exists fuzzy relational databases.(a) True(b) FalseThis question was posed to me in semester exam.My question is taken from Fuzzy Logic topic in division Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Correct answer is (a) True To EXPLAIN I would SAY: Once fuzzy RELATIONS are defined, it is possible to DEVELOP fuzzy relational databases. The first fuzzy relational database, FRDB, appeared in Maria Zemankova dissertation.

Discussion

22.	There are also other operators, more linguistic in nature, called __________ that can be applied to fuzzy set theory.(a) Hedges(b) Lingual Variable(c) Fuzz Variable(d) None of the mentionedI had been asked this question during an interview.I want to ask this question from Fuzzy Logic in division Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» RIGHT OPTION is (a) Hedges The BEST I can EXPLAIN: NONE.

Discussion

23.	Fuzzy logic is usually represented as ___________(a) IF-THEN-ELSE rules(b) IF-THEN rules(c) Both IF-THEN-ELSE rules & IF-THEN rules(d) None of the mentionedThe question was asked in an online quiz.This interesting question is from Fuzzy Logic in section Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» RIGHT choice is (b) IF-THEN RULES To explain: Fuzzy SET theory DEFINES fuzzy OPERATORS on fuzzy sets. The problem in applying this is that the appropriate fuzzy operator may not be known. For this reason, fuzzy logic usually uses IF-THEN rules, or constructs that are equivalent, such as fuzzy associative matrices. Rules are usually expressed in the form: IF variable IS property THEN action

Discussion

24.	Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the following.(a) AND(b) OR(c) NOT(d) All of the mentionedI had been asked this question in an internship interview.The question is from Fuzzy Logic in portion Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Correct answer is (d) All of the mentioned Explanation: The AND, OR, and NOT operators of BOOLEAN logic exist in fuzzy logic, usually DEFINED as the MINIMUM, MAXIMUM, and complement;

Discussion

25.	Japanese were the first to utilize fuzzy logic practically on high-speed trains in Sendai.(a) True(b) FalseI have been asked this question in class test.My question is taken from Fuzzy Logic topic in division Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The CORRECT CHOICE is (a) True The EXPLANATION: NONE.

Discussion

26.	The values of the set membership is represented by ___________(a) Discrete Set(b) Degree of truth(c) Probabilities(d) Both Degree of truth & ProbabilitiesThe question was posed to me in an online interview.This intriguing question comes from Fuzzy Logic in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Right option is (b) DEGREE of truth Explanation: Both PROBABILITIES and degree of truth ranges between 0 – 1.

Discussion

27.	The room temperature is hot. Here the hot (use of linguistic variable is used) can be represented by _______(a) Fuzzy Set(b) Crisp Set(c) Fuzzy & Crisp Set(d) None of the mentionedI got this question by my college director while I was bunking the class.Question is from Fuzzy Logic topic in division Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» RIGHT option is (a) Fuzzy Set For EXPLANATION I would say: Fuzzy LOGIC deals with linguistic VARIABLES.

Discussion

28.	Fuzzy logic is extension of Crisp set with an extension of handling the concept of Partial Truth.(a) True(b) FalseI had been asked this question during a job interview.The question is from Fuzzy Logic in section Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The CORRECT CHOICE is (a) True Easiest EXPLANATION: NONE.

Discussion

29.	The truth values of traditional set theory is ____________ and that of fuzzy set is __________(a) Either 0 or 1, between 0 & 1(b) Between 0 & 1, either 0 or 1(c) Between 0 & 1, between 0 & 1(d) Either 0 or 1, either 0 or 1I have been asked this question in quiz.The above asked question is from Fuzzy Logic in section Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Correct option is (a) EITHER 0 or 1, between 0 & 1 Explanation: Refer the definition of FUZZY set and CRISP set.

Discussion

30.	Traditional set theory is also known as Crisp Set theory.(a) True(b) FalseThis question was addressed to me in an internship interview.My doubt stems from Fuzzy Logic in portion Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The correct answer is (a) TRUE To explain: TRADITIONAL set theory set membership is fixed or exact EITHER the member is in the set or not. There is only two crisp values true or FALSE. In case of fuzzy logic there are MANY values. With weight say x the member is in the set.

Discussion

31.	What is the form of Fuzzy logic?(a) Two-valued logic(b) Crisp set logic(c) Many-valued logic(d) Binary set logicThe question was asked in quiz.My question is based upon Fuzzy Logic topic in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The CORRECT answer is (c) Many-valued logic The best EXPLANATION: With fuzzy logic set MEMBERSHIP is defined by CERTAIN value. Hence it could have many values to be in the set.

Discussion

32.	What is the consequence between a node and its predecessors while creating bayesian network?(a) Functionally dependent(b) Dependant(c) Conditionally independent(d) Both Conditionally dependant & DependantI got this question by my college director while I was bunking the class.The question is from Bayesian Networks in portion Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The correct ANSWER is (c) Conditionally independent The explanation is: The SEMANTICS to DERIVE a method for constructing bayesian networks were led to the consequence that a NODE can be conditionally independent of its PREDECESSORS.

Discussion

33.	Which condition is used to influence a variable directly by all the others?(a) Partially connected(b) Fully connected(c) Local connected(d) None of the mentionedThe question was posed to me in semester exam.This intriguing question originated from Bayesian Networks topic in division Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The CORRECT ANSWER is (B) FULLY connected Explanation: NONE.

Discussion

34.	To which does the local structure is associated?(a) Hybrid(b) Dependant(c) Linear(d) None of the mentionedThe question was asked in exam.I'm obligated to ask this question of Bayesian Networks topic in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Right option is (C) Linear Easy explanation: LOCAL structure is usually ASSOCIATED with linear rather than exponential GROWTH in complexity.

Discussion

35.	How the bayesian network can be used to answer any query?(a) Full distribution(b) Joint distribution(c) Partial distribution(d) All of the mentionedThis question was posed to me by my college director while I was bunking the class.Asked question is from Bayesian Networks topic in section Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The correct choice is (b) JOINT DISTRIBUTION To EXPLAIN: If a bayesian network is a representation of the joint distribution, then it can solve any QUERY, by summing all the relevant joint ENTRIES.

Discussion

36.	How the compactness of the bayesian network can be described?(a) Locally structured(b) Fully structured(c) Partial structure(d) All of the mentionedI had been asked this question in an online quiz.This key question is from Bayesian Networks topic in division Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The CORRECT ANSWER is (a) LOCALLY STRUCTURED The best I can explain: The compactness of the bayesian network is an example of a very GENERAL property of a locally structured system.

Discussion

37.	How the entries in the full joint probability distribution can be calculated?(a) Using variables(b) Using information(c) Both Using variables & information(d) None of the mentionedI got this question in an interview for job.This question is from Bayesian Networks topic in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» CORRECT answer is (B) Using information Easy explanation: Every ENTRY in the full JOINT probability DISTRIBUTION can be calculated from the information in the network.

Discussion

38.	Where does the bayes rule can be used?(a) Solving queries(b) Increasing complexity(c) Decreasing complexity(d) Answering probabilistic queryI got this question by my school principal while I was bunking the class.The question is from Bayesian Networks topic in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Right ANSWER is (d) ANSWERING PROBABILISTIC query Best explanation: Bayes rule can be used to answer the probabilistic QUERIES CONDITIONED on one piece of evidence.

Discussion

39.	What is needed to make probabilistic systems feasible in the world?(a) Reliability(b) Crucial robustness(c) Feasibility(d) None of the mentionedThe question was posed to me at a job interview.My question is taken from Bayesian Networks topic in portion Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Right choice is (b) CRUCIAL robustness The best EXPLANATION: On a model-based KNOWLEDGE provides the crucial robustness needed to make probabilistic system feasible in the real WORLD.

Discussion

40.	What does the bayesian network provides?(a) Complete description of the domain(b) Partial description of the domain(c) Complete description of the problem(d) None of the mentionedI have been asked this question in final exam.I'd like to ask this question from Bayesian Networks topic in portion Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Correct answer is (a) COMPLETE description of the DOMAIN For explanation: A BAYESIAN network PROVIDES a complete description of the domain.

Discussion

41.	How many terms are required for building a bayes model?(a) 1(b) 2(c) 3(d) 4The question was posed to me in quiz.I need to ask this question from Bayesian Networks topic in section Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The correct answer is (C) 3 The EXPLANATION: The three required terms are a CONDITIONAL probability and two unconditional probability.

Discussion

42.	What is meant by probability density function?(a) Probability distributions(b) Continuous variable(c) Discrete variable(d) Probability distributions for Continuous variablesI have been asked this question in a national level competition.Asked question is from Probability Notation in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The CORRECT ANSWER is (d) Probability distributions for CONTINUOUS variables Easiest explanation: NONE.

Discussion

43.	Which variable cannot be written in entire distribution as a table?(a) Discrete(b) Continuous(c) Both Discrete & Continuous(d) None of the mentionedI got this question during an interview.My doubt is from Probability Notation in division Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» RIGHT ANSWER is (b) CONTINUOUS Explanation: For continuous variables, it is not possible to WRITE out the entire distribution as a table.

Discussion

44.	How many types of random variables are available?(a) 1(b) 2(c) 3(d) 4I have been asked this question in final exam.Enquiry is from Probability Notation topic in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» CORRECT choice is (c) 3 The EXPLANATION: The three types of RANDOM variables are BOOLEAN, DISCRETE and continuous.

Discussion

45.	What is the basic element of a language?(a) Literal(b) Variable(c) Random variable(d) All of the mentionedI got this question by my college director while I was bunking the class.This interesting question is from Probability Notation topic in portion Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» The CORRECT answer is (c) Random VARIABLE The explanation: The BASIC element for a language is the random variable, which can be thought as a part of world and its STATUS is initially unknown.

Discussion

46.	Which is the complete specification of the state of the world?(a) Atomic event(b) Complex event(c) Simple event(d) None of the mentionedI got this question during an interview.This question is from Probability Notation in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Correct answer is (a) Atomic event Best EXPLANATION: An atomic event is the COMPLETE specification of the STATE of the world about which the event is UNCERTAIN.

Discussion

47.	How many formal languages are used for stating propositions?(a) 1(b) 2(c) 3(d) 4The question was posed to me during an online interview.The question is from Probability Notation topic in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Correct option is (B) 2 The explanation: The TWO FORMAL LANGUAGES used for stating propositions are PROPOSITIONAL logic and first-order logic.

Discussion

48.	Where does the dependance of experience is reflected in prior probability sentences?(a) Syntactic distinction(b) Semantic distinction(c) Both Syntactic & Semantic distinction(d) None of the mentionedThis question was posed to me in an online quiz.I'd like to ask this question from Probability Notation topic in portion Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Correct answer is (a) SYNTACTIC DISTINCTION For explanation: The dependance on EXPERIENCE is reflected in the syntactic distinction between PRIOR PROBABILITY statements.

Discussion

49.	How many issues are available in describing degree of belief?(a) 1(b) 2(c) 3(d) 4I have been asked this question during an online interview.My question is based upon Probability Notation in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» RIGHT OPTION is (b) 2 To EXPLAIN: The main issues for DEGREE of belief are nature of the sentences and the dependance of degree of the belief.

Discussion

50.	What is used for probability theory sentences?(a) Conditional logic(b) Logic(c) Extension of propositional logic(d) None of the mentionedThis question was addressed to me at a job interview.My question is taken from Probability Notation topic in division Uncertain Knowledge and Reasoning of Artificial Intelligence
Answer» Right OPTION is (c) Extension of propositional logic For explanation: The VERSION of probability theory we present USES an extension of propositional logic for its SENTENCES.

Discussion

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Input segments of AI programming contain(s)?(a) sound(b) smell(c) touch(d) none of the mentionedI got this question in an interview for internship.Asked question is from Expert Systems in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence

An AI system developed by Daniel Bobrow to read and solve algebra word problems.(a) SHRDLU(b) SIMD(c) BACON(d) STUDENTI got this question at a job interview.I'm obligated to ask this question of Expert Systems topic in section Uncertain Knowledge and Reasoning of Artificial Intelligence

Which reveals an improvement in online smoothing?(a) Matrix formulation(b) Revelation(c) HMM(d) None of the mentionedI got this question in a national level competition.Question is taken from Hidden Markov Model in portion Uncertain Knowledge and Reasoning of Artificial Intelligence

______________ is/are the way/s to represent uncertainty.(a) Fuzzy Logic(b) Probability(c) Entropy(d) All of the mentionedThis question was addressed to me in an online interview.My question comes from Fuzzy Logic in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence

Like relational databases there does exists fuzzy relational databases.(a) True(b) FalseThis question was posed to me in semester exam.My question is taken from Fuzzy Logic topic in division Uncertain Knowledge and Reasoning of Artificial Intelligence

Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the following.(a) AND(b) OR(c) NOT(d) All of the mentionedI had been asked this question in an internship interview.The question is from Fuzzy Logic in portion Uncertain Knowledge and Reasoning of Artificial Intelligence

Japanese were the first to utilize fuzzy logic practically on high-speed trains in Sendai.(a) True(b) FalseI have been asked this question in class test.My question is taken from Fuzzy Logic topic in division Uncertain Knowledge and Reasoning of Artificial Intelligence

Fuzzy logic is extension of Crisp set with an extension of handling the concept of Partial Truth.(a) True(b) FalseI had been asked this question during a job interview.The question is from Fuzzy Logic in section Uncertain Knowledge and Reasoning of Artificial Intelligence

Traditional set theory is also known as Crisp Set theory.(a) True(b) FalseThis question was addressed to me in an internship interview.My doubt stems from Fuzzy Logic in portion Uncertain Knowledge and Reasoning of Artificial Intelligence

What is the form of Fuzzy logic?(a) Two-valued logic(b) Crisp set logic(c) Many-valued logic(d) Binary set logicThe question was asked in quiz.My question is based upon Fuzzy Logic topic in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence

To which does the local structure is associated?(a) Hybrid(b) Dependant(c) Linear(d) None of the mentionedThe question was asked in exam.I'm obligated to ask this question of Bayesian Networks topic in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence

How many terms are required for building a bayes model?(a) 1(b) 2(c) 3(d) 4The question was posed to me in quiz.I need to ask this question from Bayesian Networks topic in section Uncertain Knowledge and Reasoning of Artificial Intelligence

Which variable cannot be written in entire distribution as a table?(a) Discrete(b) Continuous(c) Both Discrete & Continuous(d) None of the mentionedI got this question during an interview.My doubt is from Probability Notation in division Uncertain Knowledge and Reasoning of Artificial Intelligence

How many types of random variables are available?(a) 1(b) 2(c) 3(d) 4I have been asked this question in final exam.Enquiry is from Probability Notation topic in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence

Which is the complete specification of the state of the world?(a) Atomic event(b) Complex event(c) Simple event(d) None of the mentionedI got this question during an interview.This question is from Probability Notation in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence

How many formal languages are used for stating propositions?(a) 1(b) 2(c) 3(d) 4The question was posed to me during an online interview.The question is from Probability Notation topic in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence

How many issues are available in describing degree of belief?(a) 1(b) 2(c) 3(d) 4I have been asked this question during an online interview.My question is based upon Probability Notation in chapter Uncertain Knowledge and Reasoning of Artificial Intelligence