Description : Which reveals an improvement in online smoothing? a) Matrix formulation b) Revelation c) HMM d) None of the mentioned
Last Answer : a) Matrix formulation
Description : 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 mentioned
Last Answer : c) Single discrete random variable
Description : Which allows for a simple and matrix implementation of all the basic algorithm? a) HMM b) Restricted structure of HMM c) Temporary model
Last Answer : b) Restricted structure of HMM
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 : Which algorithm is used for solving temporal probabilistic reasoning? a) Hill-climbing search b) Hidden markov model c) Depth-first search d) Breadth-first search
Last Answer : b) Hidden markov model
Description : The concept derived from ________ level are propositional logic, tautology, predicate calculus, model, temporal logic. A. Cognition level B. Logic level C. Functional level D. All of above
Last Answer : B. Logic level
Description : 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
Last Answer : d) All of the mentioned
Description : What is meant by probability density function? a) Probability distributions b) Continuous variable c) Discrete variable d) Probability distributions for Continuous variables
Last Answer : d) Probability distributions for Continuous variables
Description : What will backward chaining algorithm will return? a) Additional statements b) Substitutes matching the query c) Logical statement d) All of the mentioned
Last Answer : b) Substitutes matching the query
Description : Which is unique up to renaming of variables? a) Unifier b) Most general unifier c) Unifier & Most general unifier d) None of the mentioned
Last Answer : b) Most general unifier
Description : Which will be the instance of the class datalog knowledge bases? a) Variables b) No function symbols c) First-order definite clauses d) None of the mentioned
Last Answer : b) No function symbols
Description : What is the condition of variables in first-order literals? a) Existentially quantified b) Universally quantified c) Both Existentially & Universally quantified d) None of the mentioned
Last Answer : b) Universally quantified
Description : PROLOG is an AI programming language which solves problems with a form of symbolic logic known as ______. A. Propositional logic B. Tautology C. Predicate calculus D. Temporal logic
Last Answer : C. Predicate calculus
Description : ______________ is/are the way/s to represent uncertainty. a) Fuzzy Logic b) Probability c) Entropy d) All of the mentioned
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 : 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 model gives the probability of each word following each other word? a) Bigram model b) Diagram model c) Gram model d) Speech model
Last Answer : a) Bigram model
Description : Which specifies the prior probability of each utterance? a) Sound model b) Model c) Language model
Last Answer : c) Language model
Description : What will happen if two literals are identical? a) Remains the same b) Added as three c) Reduced to one d) None of the mentioned
Last Answer : c) Reduced to one
Description : The component of an ICAI (Intelligent Computer Assisted Instruction) presenting information to the student is the? a) Student model b) Problem solving expertise c) Tutoring module d) All of the mentioned
Last Answer : c) Tutoring module
Description : Which are partially captured by triphone model? a) Articulation effects b) Coarticulation effects c) Both Articulation & Coarticulation effects d) None of the mentioned
Last Answer : b) Coarticulation effects
Description : 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
Last Answer : c) Three-state phone mone
Description : Which of the following is the component of learning system? a) Goal b) Model c) Learning rules d) All of the mentioned
Description : 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 mentioned
Last Answer : a) Speech recognition
Description : Which of the following is the model used for learning? a) Decision trees b) Neural networks c) Propositional and FOL rules d) All of the mentioned
Description : is an extension of the wireframe model with additional face information added. a.CSG b.B-rep c.Loft d.none of the above
Last Answer : b.B-rep
Description : What is the process of associating a FOL expression with a phrase? a) Interpretation b) Augmented reality c) Semantic interpretation d) Augmented interpretation
Last Answer : c) Semantic interpretation
Description : An omniscient agent knows the actual outcome of its actions and can act accordingly; but omniscience is impossible in reality. Rational Agent always does the right thing; but Rationality is possible in reality. a) True b) False
Last Answer : a) True
Description : How many types of random variables are available? a) 1 b) 2 c) 3 d) 4
Last Answer : c) 3
Description : Where does the degree of belief is applied? a) Propositions b) Literals c) Variables d) Statements
Last Answer : a) Propositions
Description : The primitives in probabilistic reasoning are random variables. a) True b) False
Description : A Hybrid Bayesian network contains ___________ a) Both discrete and continuous variables b) Only Discrete variables c) Only Discontinuous variable
Last Answer : a) Both discrete and continuous variables
Description : What are present in each level of planning graph? a) Literals b) Actions c) Variables d) Both Literals & Actions
Last Answer : d) Both Literals & Actions
Description : What is the process of capturing the inference process as a single inference rule? a) Ponens b) Clauses c) Generalized Modus Ponens d) Variables
Last Answer : c) Generalized Modus Ponens
Description : The rule of Universal Instantiation (UI for short) says that we can infer any sentence obtained by substituting a ground term (a term without variables) for the variable. a) True b) False
Description : What kind of clauses are available in Conjunctive Normal Form? a) Disjunction of literals b) Disjunction of variables c) Conjunction of literals d) Conjunction of variables
Last Answer : a) Disjunction of literals
Description : Which is a refutation complete inference procedure for propositional logic? a) Clauses b) Variables c) Propositional resolution d) Proposition
Last Answer : c) Propositional resolution
Description : Define runtime variables.
Last Answer : Plans to gather and use information are represented using short hand Notation called runtime variables (n). Example [Look up (Agent, “Phone number (Divya)”.N), Dial (n)]
Description : What is used for probability theory sentences? a) Conditional logic b) Logic 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 : Stochastic hill climbing chooses at random from among the uphill moves; the probability of selection can vary with the steepness of the uphil1 move. a) True b) False
Description : In Bayes theorem, what is meant by P(Hi|E)? a) The probability that hypotheses Hi is true given evidence E b) The probability that hypotheses Hi is false given evidence E c) The probability ... Hi is true given false evidence E d) The probability that hypotheses Hi is false given false evidence E
Last Answer : a) The probability that hypotheses Hi is true given evidence E
Description : Subject orientation A . The science of collecting, organizing, and applying numerical facts B. Measure of the probability that a certain hypothesis is incorrect given certain observations. C. ... specially built around all the existing applications of the operational data D . None of these
Last Answer : C. One of the defining aspects of a data warehouse, which is specially built around all the existing applications of the operational data
Description : Define joint probability distribution
Last Answer : This completely specifies an agent's probability assignments to all propositions in the domain.The joint probability distribution p(x1,x2,--------xn) assigns probabilities to all possible atomic events;where X1,X2------Xn 10 =variables.
Description : Define probability distribution
Last Answer : Eg. P(weather) = (0.7,0.2,0.08,0.02). This type of notations simplifies many equations.
Description : Define conditional probability?
Last Answer : Once the agents has obtained some evidence concerning the previously unknown propositions making up the domain conditional or posterior probabilities with the notation p(A/B) is used. This is important that p(A/B) can only be used when all be is known.