Description : ______________ is/are the way/s to represent uncertainty. a) Fuzzy Logic b) Probability c) Entropy d) All of the mentioned
Last Answer : d) All of the mentioned
Description : Many words have more than one meaning; we have to select the meaning which makes the most sense in context. This can be resolved by ____________ a) Fuzzy Logic b) Word Sense Disambiguation c) Shallow Semantic Analysis d) All of the mentioned
Last Answer : b) Word Sense Disambiguation
Description : ____________ are algorithms that learn from their more complex environments (hence eco) to generalize, approximate and simplify solution logic. a) Fuzzy Relational DB b) Ecorithms c) Fuzzy Set d) None of the mentioned
Last Answer : c) Fuzzy Set
Description : ______ are algorithms that learn from their more complex environments (hence eco) to generalize, approximate and simplify solution logic. a) Fuzzy Relational DB b) Ecorithms c) Fuzzy Set d) None of the mentioned
Description : Fuzzy logic is usually represented as a) IF-THEN-ELSE rules b) IF-THEN rules c) Both a & b d) None of the mentioned
Last Answer : b) IF-THEN rules
Description : Which of the following is used for probability theory sentences? a) Conditional logic b) Logic c) Extension of propositional logic d) None of the mentioned
Last Answer : c) Extension of propositional logic
Description : Which is true for Decision theory? a) Decision Theory = Probability theory + utility theory b) Decision Theory = Inference theory + utility theory c) Decision Theory = Uncertainty + utility theory d) Decision Theory = Probability theory + preference
Last Answer : c) Decision Theory = Uncertainty + utility theory
Description : Computers normally solve problem by breaking them down into a series of yes-or-no decisions represented by 1s and 0s. What is the name of the logic that allows computers to assign numerical values that fail ... 0 and 1? a) Human logic b) Fuzzy logic c) Boolean logic d) Operational logic
Last Answer : b) Fuzzy logic
Description : How is Fuzzy Logic different from conventional control methods? a) IF and THEN Approach b) FOR Approach c) WHILE Approach d) DO Approach
Last Answer : a) IF and THEN Approach
Description : Fuzzy logic is usually represented as ___________ a) IF-THEN-ELSE rules b) IF-THEN rules c) Both IF-THEN-ELSE rules & IF-THEN rules
Description : Japanese were the first to utilize fuzzy logic practically on high-speed trains in Sendai. a) True b) False
Last Answer : a) True
Description : Fuzzy logic is extension of Crisp set with an extension of handling the concept of Partial Truth. a) True b) False
Description : What is the form of Fuzzy logic? a) Two-valued logic b) Crisp set logic c) Many-valued logic d) Binary set logic
Last Answer : c) Many-valued logic
Description : Conventional Artificial Intelligence is different from soft computing in the sense A. Conventional Artificial Intelligence deal with prdicate logic where as soft computing deal with fuzzy logic B. Conventional Artificial ... empirical data C. Both (a) and (b) D. None of the above
Last Answer : C. Both (a) and (b
Description : Fuzzy Computing A . mimics human behaviour B. doesnt deal with 2 valued logic C. deals with information which is vague, imprecise, uncertain, ambiguous, inexact, or probabilistic D . All of the above
Last Answer : D . All of the above
Description : How is Fuzzy Logic different from conventional control methods? a) IF and THEN Approach b) FOR Approach c) WHILE Approach d) DO Approach e) Else If approach
Description : Fuzzy logic is a form of a) Two-valued logic b) Crisp set logic c) Many-valued logic d) Binary set logic
Description : 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. What is name of AI? A. Boolean logic B. Human logic C. Fuzzy logic D. Functional logic
Last Answer : C. Fuzzy logic
Description : 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 mentioned
Last Answer : a) Hedges
Description : Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the following. a) AND b) OR c) NOT d) All of the mentioned
Description : 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 mentioned
Last Answer : a) Fuzzy Set
Description : What is used for probability theory sentences? a) Conditional logic b) Logic c) Extension of propositional logic
Description : Ambiguity may be caused by ______________ a) syntactic ambiguity b) multiple word meanings c) unclear antecedents d) all of the mentioned
Last Answer : d) all of the mentioned
Description : Using logic to represent and reason we can represent knowledge about the world with facts and rules. a) True b) False
Description : Where does the additional variables are added in HMM? a) Temporal model b) Reality model c) Probability model d) All of the mentioned
Last Answer : a) Temporal model
Description : 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 mentioned
Last Answer : b) Using information
Description : 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 mentioned
Last Answer : a) Syntactic distinction
Description : What is Morphological Segmentation? a) Does Discourse Analysis b) Separate words into individual morphemes and identify the class of the morphemes c) Is an extension of propositional logic d) None of the mentioned
Last Answer : b) Separate words into individual morphemes and identify the class of the morphemes
Description : Which is an appropriate language for describing the relationships? a) First-order logic b) Propositional logic c) ILP d) None of the mentioned
Last Answer : a) First-order logic
Description : Which can be converted to inferred equivalent CNF sentence? a) Every sentence of propositional logic b) Every sentence of inference c) Every sentence of first-order logic d) All of the mentioned
Last Answer : c) Every sentence of first-order logic
Description : First Order Logic is also known as ___________ a) First Order Predicate Calculus b) Quantification Theory c) Lower Order Calculus d) All of the mentioned
Description : The statement comprising the limitations of FOL is/are ____________ a) Expressiveness b) Formalizing Natural Languages c) Many-sorted Logic d) All of the mentioned
Description : Which kind of agent architecture should an agent an use? a) Relaxed b) Logic c) Relational d) All of the mentioned
Description : What is not represented by using propositional logic? a) Objects b) Relations c) Both Objects & Relations d) None of the mentioned
Last Answer : c) Both Objects & Relations
Description : Uncertainty arises in the wumpus world because the agent’s sensors give only ___________ a) Full & Global information b) Partial & Global Information c) Partial & local Information d) Full & local information
Last Answer : c) Partial & local Information
Description : Why does uncertainty arise ?
Last Answer : Agents almost never have access to the whole truth about their environment. Agents cannot find a caterorial answer. Uncertainty can also arise because of incompleteness, incorrectness in agents understanding of properties of environmen
Description : Like relational databases there does exists fuzzy relational databases. a) True b) False
Description : 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 1
Last Answer : a) Either 0 or 1, between 0 & 1
Description : The crossover points of a membership function are defined as the elements in the universe for which a particular fuzzy set has values equal to A. infinite B. 1 C. 0 D. 0.5
Last Answer : D. 0.5
Description : The membership values of the membership function are nor strictly monotonically increasing or decreasing or strictly monoronically increasing than decreasing. A. Convex Fuzzy Set B. Non convex fuzzy set C. Normal Fuzzy set D. Sub normal fuzzy set
Last Answer : B. Non convex fuzzy set
Description : A fuzzy set has a membership function whose membership values are strictly monotonically increasing or strictly monotonically decreasing or strictly monotonically increasing than strictly monotonically decreasing with increasing ... fuzzy set C. Non concave Fuzzy set D. Non Convex Fuzzy set
Last Answer : A. convex fuzzy set
Description : A fuzzy set wherein no membership function has its value equal to 1 is called A. normal fuzzy set B. subnormal fuzzy set. C. convex fuzzy set D. concave fuzzy set
Last Answer : B. subnormal fuzzy set.
Description : In a Fuzzy set a prototypical element has a value A. 1 B. 0 C. infinite D. Not defined
Last Answer : A. 1
Description : The region of universe that is characterized by complete membership in the set is called A. Core B. Support C. Boundary D. Fuzzy
Last Answer : A. Core
Description : Three main basic features involved in characterizing membership function are A. Intution, Inference, Rank Ordering B. Fuzzy Algorithm, Neural network, Genetic Algorithm C. Core, Support , Boundary D. Weighted Average, center of Sums, Median
Last Answer : C. Core, Support , Boundary
Description : Membership function defines the fuzziness in a fuzzy set irrespective of the elements in the set, which are discrete or continuous. A. True B. False
Last Answer : B. False
Description : Core of soft Computing is A. Fuzzy Computing, Neural Computing, Genetic Algorithms B. Fuzzy Networks and Artificial Intelligence C. Artificial Intelligence and Neural Science D. Neural Science and Genetic Science
Last Answer : D. Neural Science and Genetic Science