Description : Which is used for utility functions in game playing algorithm? a) Linear polynomial b) Weighted polynomial c) Polynomial d) Linear weighted polynomial
Last Answer : d) Linear weighted polynomial
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 : Which is the best way to go for Game playing problem? a) Linear approach b) Heuristic approach (Some knowledge is stored) c) Random approach d) An Optimal approach
Last Answer : b) Heuristic approach (Some knowledge is stored)
Description : The action of the Simple reflex agent completely depends upon __________ a) Perception history b) Current perception c) Learning theory d) Utility functions
Last Answer : b) Current perception
Description : Zero sum games are the one in which there are two agents whose actions must alternate and in which the utility values at the end of the game are always the same. a) True b) False
Last Answer : b) False
Description : General algorithm applied on game tree for making decision of win/lose is ____________ a) DFS/BFS Search Algorithms b) Heuristic Search Algorithms c) Greedy Search Algorithms d) MIN/MAX Algorithms
Last Answer : d) MIN/MAX Algorithms
Description : Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions
Last Answer : a) Linear Functions
Description : Neural Networks are complex ______________with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions
Last Answer : b) Nonlinear Functions
Description : Neural Networks are complex ———————–with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions e) Power Functions
Description : 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. ... have to be explicitly hand-coded d) False - just having a single perceptron is enough
Last Answer : c) True – perceptrons can do this but are unable to learn to do it – they have to be explicitly hand-coded
Description : 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
Last Answer : b) Heaviside function
Description : 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
Last Answer : a) True
Description : 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
Last Answer : d) All of the mentioned
Description : How the distance between two shapes can be defined? a) Weighted sum of the shape b) Size of the shape c) Shape context d) None of the mentioned
Last Answer : a) Weighted sum of the shape
Description : Artificial Intelligence has its expansion in the following application. a) Planning and Scheduling b) Game Playing c) Diagnosis d) All of the mentioned
Description : What is Artificial intelligence? a) Putting your intelligence into Computer b) Programming with your own intelligence c) Making a Machine intelligent d) Playing a Game
Last Answer : c) Making a Machine intelligent
Description : Discuss Game playing. Explain Alpha-beta pruning.
Last Answer : Ans. Game playing Games are well-defined problems that are generally interpreted as requiring intelligence to play well. Introduces uncertainty since opponents moves can not be ... such as utility values distributed randomly across leaves and therefore experimental results are necessary.
Description : Artificial Intelligence has its expansion in the following application. a. Planning and Scheduling b. Game Playing c. Robotics d. All of the above
Last Answer : d. All of the above
Description : Artificial Intelligence has its expansion in the following application. A. Planning and Scheduling B. Game Playing C. Robotics D. All of the above
Last Answer : D. All of the above
Description : The travelling salesman problem can be solved in: (A) Polynomial time using dynamic programming algorithm (B) Polynomial time using branch-and-bound algorithm (C) Exponential time using dynamic programming algorithm or branch-andbound algorithm. (D) Polynomial time using backtracking algorithm.
Last Answer : (C) Exponential time using dynamic programming algorithm or branch-andbound algorithm.
Description : 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
Last Answer : a) Decision tree
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 : Which agent deals with happy and unhappy states? a) Simple reflex agent b) Model based agent c) Learning agent d) Utility based agent
Last Answer : d) Utility based agent
Description : An algorithm A is admissible if ___________ a) It is not guaranteed to return an optimal solution when one exists b) It is guaranteed to return an optimal solution when one exists c) It returns more solutions, but not an optimal one d) It guarantees to return more optimal solutions
Last Answer : b) It is guaranteed to return an optimal solution when one exists
Description : An algorithm is complete if ____________ a) It terminates with a solution when one exists b) It starts with a solution c) It does not terminate with a solution d) It has a loop
Last Answer : a) It terminates with a solution when one exists
Description : Decision Tree is a display of an algorithm. a) True b) False
Description : A perceptron is a ______________ a) Feed-forward neural network b) Backpropagation algorithm c) Backtracking algorithm d) Feed Forward-backward algorithm
Last Answer : a) Feed-forward neural network
Description : Which suggests the existence of an efficient recursive algorithm for online smoothing? a) Matrix b) Constant space c) Constant time d) None of the mentioned
Last Answer : b) Constant space
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 : 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 : __________ algorithm translates a planning problem in to prepositional axioms. a) GraphPlan b) SatPlan c) Greedy d) None of the mentioned
Last Answer : b) SatPlan
Description : Which is used to extract solution directly from the planning graph? a) Planning algorithm b) Graphplan c) Hill-climbing search d) All of the mentioned
Last Answer : b) Graphplan
Description : Which data structure is used to give better heuristic estimates? a) Forwards state-space b) Backward state-space c) Planning graph algorithm d) None of the mentioned
Last Answer : c) Planning graph algorithm
Description : Which algorithm places two actions into a plan without specifying which should come first? a) Full-order planner b) Total-order planner c) Semi-order planner d) Partial-order planner
Last Answer : d) Partial-order planner
Description : Sussman Anomaly illustrates a weakness of interleaved planning algorithm. a) True b) False
Description : Which makes the complexity of the entire algorithm quadratic in the size? a) Clause b) Inference c) Resolution d) Occur check
Last Answer : d) Occur check
Description : Which algorithm takes two sentences and returns a unifier? a) Inference b) Hill-climbing search c) Depth-first search d) Unify algorithm
Last Answer : d) Unify algorithm
Description : An inference algorithm that derives only entailed sentences is called sound or truth-preserving. a) True b) False
Description : Which is omitted in prolog unification algorithm? a) Variable check b) Occur check c) Proposition check d) Both Occur & Proposition check
Last Answer : b) Occur check
Description : Which problem can frequently occur in backward chaining algorithm? a) Repeated states b) Incompleteness c) Complexity d) Both Repeated states & Incompleteness
Last Answer : d) Both Repeated states & Incompleteness
Description : Which algorithm are in more similar to backward chaining algorithm? a) Depth-first search algorithm b) Breadth-first search algorithm c) Hill-climbing search algorithm d) All of the mentioned
Last Answer : a) Depth-first search algorithm
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 algorithm will work backward from the goal to solve a problem? a) Forward chaining b) Backward chaining c) Hill-climb algorithm d) None of the mentioned
Last Answer : b) Backward chaining
Description : Which are needed to compute the logical inference algorithm? a) Logical equivalence b) Validity c) Satisfiability d) All of the mentioned
Description : Which values are independant in minimax search algorithm? a) Pruned leaves x and y b) Every states are dependant c) Root is independant d) None of the mentioned
Last Answer : a) Pruned leaves x and y
Description : Which approach is to pretend that a pure divide and conquer algorithm will work? a) Goal independence b) Subgoal independence c) Both Goal & Subgoal independence d) None of the mentioned
Last Answer : b) Subgoal independence
Description : Which is the most straightforward approach for planning algorithm? a) Best-first search b) State-space search c) Depth-first search d) Hill-climbing search
Last Answer : b) State-space search