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 : Breadth-first search is not optimal when all step costs are equal, because it always expands the shallowest unexpanded node. a) True b) False
Last Answer : b) False
Description : A* is optimal if h(n) is an admissible heuristic-that is, provided that h(n) never underestimates the cost to reach the goal. a) True b) False
Last Answer : a) True
Description : A solution to a problem is a path from the initial state to a goal state. Solution quality is measured by the path cost function, and an optimal solution has the highest path cost among all solutions. a) True b) False
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 : Hill climbing sometimes called ____________ because it grabs a good neighbor state without thinking ahead about where to go next. a) Needy local search b) Heuristic local search c) Greedy local search d) Optimal local search
Last Answer : c) Greedy local search
Description : Though local search algorithms are not systematic, key advantages would include __________ a) Less memory b) More time c) Finds a solution in large infinite space d) Less memory & Finds a solution in large infinite space
Last Answer : d) Less memory & Finds a solution in large infinite space
Description : Which search is complete and optimal when h(n) is consistent? a) Best-first search b) Depth-first search c) Both Best-first & Depth-first search d) A* search
Last Answer : d) A* search
Description : The BACKTRACKING-SEARCH algorithm in Figure 5.3 has a very simple policy for what to do when a branch of the search fails: back up to the preceding variable and try a different value for it. This is ... also possible to go all the way to set of variable that caused failure. a) True b) False
Description : A genetic algorithm (or GA) is a variant of stochastic beam search in which successor states are generated by combining two parent states, rather than by modifying a single state. a) True b) False
Description : There exists two way to infer using semantic networks in which knowledge is represented as Frames. 1) Intersection Search 2) Inheritance Search a) True b) False
Last Answer : 1) Intersection Search
Description : __________ algorithm keeps track of k states rather than just one. a) Hill-Climbing search b) Local Beam search c) Stochastic hill-climbing search d) Random restart hill-climbing search
Last Answer : b) Local Beam search
Description : A perceptron is a ——————————–. a) Feed-forward neural network b) Back-propagation algorithm c) Back-tracking algorithm d) Feed Forward-backward algorithm e) Optimal algorithm with Dynamic programming
Last Answer : a) Feed-forward neural network
Description : The name best-first search is a venerable but inaccurate one. After all, if we could really expand the best node first, it would not be a search at all; it would be a straight march to the ... is choose the node that appears to be best according to the evaluation function. a) True b) False
Description : The main idea of Bidirectional search is to reduce the time complexity by searching two way simultaneously from start node and another from goal node. a) True b) False
Description : What are the main cons of hill-climbing search? a) Terminates at local optimum & Does not find optimum solution b) Terminates at global optimum & Does not find optimum solution c) Does not find optimum solution & Fail to find a solution
Last Answer : a) Terminates at local optimum & Does not find optimum solution
Description : Greedy search strategy chooses the node for expansion in ___________ a) Shallowest b) Deepest c) The one closest to the goal node d) Minimum heuristic cost
Last Answer : c) The one closest to the goal node
Description : Consider the following statements: (a) Depth - first search is used to traverse a rooted tree. (b) Pre - order, Post-order and Inorder are used to list the vertices of an ordered rooted tree. (c) Huffman's algorithm is used to find an optimal ... (d) (C) (a) , (b) and (c) (D) (a), (b) , (c) and (d)
Last Answer : (D) (a), (b) , (c) and (d)
Description : If h* represents an estimate of the cost of getting from the current node N to the goal node and h represents actual cost of getting from current node to the goal node, then A* algorithm gives an optimal solution ... h* us equal to h (B) h* overestimates h (C) h* underestimates h (D) none of these
Last Answer : (C) h* underestimates h
Description : When is breadth-first search is optimal? a) When there is less number of nodes b) When all step costs are equal c) When all step costs are unequal
Last Answer : b) When all step costs are equal
Description : Which search method takes less memory? a) Depth-First Search b) Breadth-First search c) Linear Search d) Optimal search
Last Answer : a) Depth-First Search
Description : Which search method takes less memory? a) Depth-First Search b) Breadth-First search c) Optimal search d) Linear Search
Description : Which is true regarding BFS (Breadth First Search)? a) BFS will get trapped exploring a single path b) The entire tree so far been generated must be stored in BFS c) BFS is not guaranteed to find a solution if exists d) BFS is nothing but Binary First Search
Last Answer : b) The entire tree so far been generated must be stored in BFS
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 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 : When will Hill-Climbing algorithm terminate? a) Stopping criterion met b) Global Min/Max is achieved c) No neighbor has higher value d) All of the mentioned
Last Answer : c) No neighbor has higher value
Description : Decision Tree is a display of an algorithm. a) True b) False
Description : Sussman Anomaly illustrates a weakness of interleaved planning algorithm. a) True b) False
Description : An inference algorithm that derives only entailed sentences is called sound or truth-preserving. a) True b) False
Description : The minimax algorithm computes the minimax decision from the current state. It uses a simple recursive computation of the minimax values of each successor state, directly implementing the defining equations. The ... are backed up through the tree as the recursion unwinds. a) True b) False
Description : Like relational databases there does exists fuzzy relational databases. a) True b) False
Description : 50. Which of the following statements is true with respect to the optimal solution of an LP problem? a. Every LP problem has an optimal solution b. Optimal solution of an LP problem always occurs ... completely used d. If an optimal solution exists, there will always be at least one at a corner
Last Answer : d. If an optimal solution exists, there will always be at least one at a corner
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 : 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 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 : 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 : 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 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
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 : Which of the following algorithm is generally used CSP search algorithm? a) Breadth-first search algorithm b) Depth-first search algorithm c) Hill-climbing search algorithm d) None of the mentioned
Last Answer : b) Depth-first search algorithm
Description : The term ___________ is used for a depth-first search that chooses values for one variable at a time and returns when a variable has no legal values left to assign. a) Forward search b) Backtrack search c) Hill algorithm d) Reverse-Down-Hill search
Last Answer : b) Backtrack search
Description : ______________ Is an algorithm, a loop that continually moves in the direction of increasing value – that is uphill. a) Up-Hill Search b) Hill-Climbing c) Hill algorithm d) Reverse-Down-Hill search
Last Answer : b) Hill-Climbing
Description : A* algorithm is based on ___________ a) Breadth-First-Search b) Depth-First –Search c) Best-First-Search d) Hill climbing
Last Answer : c) Best-First-Search
Description : Which search algorithm imposes a fixed depth limit on nodes? a) Depth-limited search b) Depth-first search c) Iterative deepening search d) Bidirectional search
Last Answer : a) Depth-limited search
Description : Which algorithm is used to solve any kind of problem? a) Breadth-first algorithm b) Tree algorithm c) Bidirectional search algorithm d) None of the mentioned
Last Answer : b) Tree algorithm
Description : A search algorithm takes _________ as an input and returns ________ as an output. a) Input, output b) Problem, solution c) Solution, problem d) Parameters, sequence of actions
Last Answer : b) Problem, solution
Description : Which search algorithm will use limited amount of memory? a) RBFS b) SMA* c) Hill-climbing search algorithm d) Both RBFS & SMA*
Last Answer : d) Both RBFS & SMA*
Description : Genetic Algorithm are a part of A . Evolutionary Computing B. inspired by Darwin's theory about evolution - "survival of the fittest" C. are adaptive heuristic search algorithm based on the evolutionary ideas of natural selection and genetics D . All of the above
Last Answer : D . All of the above
Description : Depth-first search always expands the ______ node in the current fringe of the search tree. a) Shallowest b) Child node c) Deepest d) Minimum cost
Last Answer : c) Deepest