Description : A problem in a search space is defined by one of these state. a) Initial state b) Last state c) Intermediate state d) All of the mentioned
Last Answer : a) Initial state
Description : A game can be formally defined as a kind of search problem with the following components. a) Initial State b) Successor Function c) Terminal Test d) All of the mentioned
Last Answer : d) All of the mentioned
Description : In which of the following situations might a blind search be acceptable? a) Real life situation b) Complex game c) Small search space d) All of the mentioned
Last Answer : c) Small search space
Description : In which of the following situations might a blind search be acceptable? a) real-life situation b) complex game c) small search space d) all of the mentioned
Last Answer : c) small search space
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 : The time and space complexity of BFS is (For time and space complexity problems consider b as branching factor and d as depth of the search tree.) a) O(bd+1) and O(bd+1) b) O(b2) and O(d2) c) O(d2) and O(b2) d) O(d2) and O(d2)
Last Answer : a) O(bd+1) and O(bd+1)
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 : 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 : What is the problem space of means-end analysis? a) An initial state and one or more goal states b) One or more initial states and one goal state c) One or more initial states and one or more goal state d) One initial state and one goal state
Last Answer : a) An initial state and one or more goal states
Description : The Set of actions for a problem in a state space is formulated by a ___________ a) Intermediate states b) Initial state c) Successor function, which takes current action and returns next immediate state d) None of the mentioned
Last Answer : c) Successor function, which takes current action and returns next immediate state
Description : Define search tree.
Last Answer : The tree which is constructed for the search process over the state space is called search tree.
Description : A heuristic is a way of trying __________ a) To discover something or an idea embedded in a program b) To search and measure how far a node in a search tree seems to be from a goal c) To compare two nodes in a search tree to see if one is better than the other is d) All of the mentioned
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 : Which of the following search belongs to totally ordered plan search? a) Forward state-space search b) Hill-climbing search c) Depth-first search d) Breadth-first search
Last Answer : a) Forward state-space search
Description : What is the other name of the backward state-space search? a) Regression planning b) Progression planning c) State planning d) Test planning
Last Answer : a) Regression planning
Description : What is the main advantage of backward state-space search? a) Cost b) Actions c) Relevant actions d) All of the mentioned
Last Answer : c) Relevant actions
Description : How many states are available in state-space search? a) 1 b) 2 c) 3 d) 4
Last Answer : d) 4
Description : What is the other name for forward state-space search? a) Progression planning b) Regression planning c) Test planning d) None of the mentioned
Last Answer : a) Progression planning
Description : How many ways are available to solve the state-space search? a) 1 b) 2 c) 3 d) 4
Last Answer : b) 2
Description : What are taken into account of state-space search? a) Postconditions b) Preconditions c) Effects d) Both Preconditions & Effects
Last Answer : d) Both Preconditions & Effects
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 : Which method is used to search better by learning? a) Best-first search b) Depth-first search c) Metalevel state space d) None of the mentioned
Last Answer : c) Metalevel state space
Description : Which search uses only the linear space for searching? a) Best-first search b) Recursive best-first search c) Depth-first search d) None of the mentioned
Last Answer : b) Recursive best-first search
Description : What is the space complexity of Depth-first search? a) O(b) b) O(bl) c) O(m) d) O(bm)
Last Answer : d) O(bm)
Description : Search space A . The large set of candidate solutions possible for a problem B. The information stored in a database that can be, retrieved with a single query. C. Worth of the output of a machine learning program that makes it understandable for humans D . None of these
Last Answer : A . The large set of candidate solutions possible for a problem
Description : Write the time & space complexity associated with depth limited search.
Last Answer : Time complexity =O (bd) , b-branching factor, d-depth of tree Space complexity=o (bl)
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 : To eliminate the inaccuracy problem in planning problem or partial order planning problem we can use ___________________ data structure/s. a) Stacks b) Queue c) BST (Binary Search Tree) d) Planning Graphs
Last Answer : d) Planning Graphs
Description : A heuristic is a way of trying ___________ a) To discover something or an idea embedded in a program b) To search and measure how far a node in a search tree seems to be from a goal c) To compare two nodes in a search tree to see if one is better than another d) All of the mentioned
Description : Breadth-first search always expands the ______ node in the current fringe of the search tree. a) Shallowest b) Child node c) Deepest
Last Answer : a) Shallowest
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
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 : Define Online Search agent.
Last Answer : Agent operates by interleaving computation and action (i.e.) first it takes an action, and then it observes the environment and computes the next action.
Description : Define Hill Climbing search.
Last Answer : It is a loop that continually moves in a increasing value direction (i.e.) up hill and terminates when it reaches a “peak” where no neighbor has a higher value.
Description : Define iterative deepening search.
Last Answer : Iterative deepening is a strategy that sidesteps the issue of choosing the best depth limit by trying all possible depth limits: first depth 0, then depth 1,then depth 2& so on.
Description : Define A* search.
Last Answer : A* search evaluates nodes by combining g(n), the cost to reach the node and h(n), the cost to get from the node to the goal. f(n) = g(n) + h(n)
Description : Define Greedy Best First Search.
Last Answer : It expands the node that is closest to the goal (i.e.) to reach solution in a quicker way. It is done by using the heuristic function: f(n) = h(n).
Description : Define depth limited search.
Last Answer : The problem of unbounded tress can be avoided by supplying depth limit 1(i.e.) nodes at depth 1 are treated as if they have no successors. This is called Depth Limited search.
Description : Define Depth first search.
Last Answer : It expands the deepest node in the current fringe of the search tree.
Description : Define Uniform cost search.
Last Answer : Uniform cost search expands the node ‘n’ with the lowest path cost instead of expanding the shallowest node.
Description : Define Backtracking search.
Last Answer : The variant of depth first search called backtracking search. Only one successor is generated at a time rather than all successor, partially expanded node remembers which successor generate next is called Backtracking search.
Description : Define search node.
Last Answer : The root of the search tree that is the initial state of the problem is called search node.
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 : uniform-cost search expands the node n with the __________ a) Lowest path cost b) Heuristic cost c) Highest path cost d) Average path cost
Last Answer : a) Lowest path cost
Description : Define State Space.
Last Answer : The set of all possible states reachable from the initial state by any sequence of action is called state space.
Description : What will happen if a predecessor description is generated that is satisfied by the initial state of the planning problem? a) Success b) Error c) Compilation d) Termination
Last Answer : d) Termination
Description : Flexible CSPs relax on _______ a) Constraints b) Current State c) Initial State d) Goal State
Last Answer : a) Constraints
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
Last Answer : a) True
Description : In 1985, the famous chess player David Levy beat a world champion chess program in four straight games by using orthodox moves that confused the program. What was the name of the chess program? a) Kaissa b) CRAY BLITZ c) Golf d) DIGDUG
Last Answer : b) CRAY BLITZ
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