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

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
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b) Graphplan
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__________ algorithm translates a planning problem in to prepositional axioms. a) GraphPlan b) SatPlan c) Greedy d) None of the mentioned

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

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

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

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

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

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

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

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

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

Which algorithm takes two sentences and returns a unifier? a) Inference b) Hill-climbing search c) Depth-first search d) Unify algorithm

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

__________ 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

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

______________ 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

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

A* algorithm is based on ___________ a) Breadth-First-Search b) Depth-First –Search c) Best-First-Search d) 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

Which search algorithm will use limited amount of memory? a) RBFS b) SMA* c) Hill-climbing search algorithm d) Both RBFS & SMA*

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*

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

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

____________ planning allows the agent to take advice from the domain designer in the form of decomposition rules. a) GraphPlan b) Hierarchical task network (HTN) c) SatPlan d) None of the mentioned

Description : ____________ planning allows the agent to take advice from the domain designer in the form of decomposition rules. a) GraphPlan b) Hierarchical task network (HTN) c) SatPlan d) None of the mentioned

Last Answer : b) Hierarchical task network (HTN)

_____________ algorithms is used to extract the plan directly from the planning graph, rather than using graph to provide heuristic. a) BFS/DFS b) A* c) Graph-Plan d) Greedy

Description : _____________ algorithms is used to extract the plan directly from the planning graph, rather than using graph to provide heuristic. a) BFS/DFS b) A* c) Graph-Plan d) Greedy

Last Answer : c) Graph-Plan

Which search is similar to minimax search? a) Hill-climbing search b) Depth-first search c) Breadth-first search d) All of the mentioned

Description : Which search is similar to minimax search? a) Hill-climbing search b) Depth-first search c) Breadth-first search d) All of the mentioned

Last Answer : b) Depth-first search

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

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

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

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

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

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

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

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

Define Hill Climbing search.

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. 

What is the name of algorithm in which 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 : Platue climbing valley

Description : What is the name of algorithm in which 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 : Platue climbing valley

Last Answer : B : Hill-Climbing

What is the name of algorithm in which 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 : Platue climbing valley

Description : What is the name of algorithm in which 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 : Platue climbing valley

Last Answer : B : Hill-Climbing

A* algorithm is based on which of the following concept? A : Best-First-Search B : Breadth-First-Search C : Depth-First –Search D : Hill climbing

Description : A* algorithm is based on which of the following concept? A : Best-First-Search B : Breadth-First-Search C : Depth-First –Search D : Hill climbing

Last Answer : A : Best-First-Search

What is the name of algorithm in which 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 : Platue climbing valley

Description : What is the name of algorithm in which 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 : Platue climbing valley

Last Answer : B : Hill-Climbing

What is the name of algorithm in which 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 : Platue climbing valley

Description : What is the name of algorithm in which 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 : Platue climbing valley

Last Answer : B : Hill-Climbing

A* algorithm is based on (A) Breadth-First-Search (B) Depth-First –Search (C) Best-First-Search (D) 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

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

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

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

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

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

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

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

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

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

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

When will further expansion is unnecessary for planning graph? a) Identical b) Replicate c) Not identical d) None of the mentioned

Description : When will further expansion is unnecessary for planning graph? a) Identical b) Replicate c) Not identical d) None of the mentioned

Last Answer : a) Identical

Which kind of problem are suitable for planning graph? a) Propositional planning problem b) Planning problem c) Action problem d) None of the mentioned

Description : Which kind of problem are suitable for planning graph? a) Propositional planning problem b) Planning problem c) Action problem d) None of the mentioned

Last Answer : a) Propositional planning problem

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 : 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

Last Answer : a) True

What are the variants of hill climbing?

Description : What are the variants of hill climbing?

Last Answer : i. Stochastic hill climbing  ii. First choice hill climbing  iii. Simulated annealing search  iv. Local beam search  v. Stochastic beam search

List some drawbacks of hill climbing process.

Description : List some drawbacks of hill climbing process. 

Last Answer : Local maxima: A local maxima as opposed to a goal maximum is a peak that is lower that the highest peak in the state space. Once a local maxima is reached the algorithm will halt even though ... of the state space where the evaluation fn is essentially flat. The search will conduct a random walk.

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 D : Fail to find a solution

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 D : Fail to find a solution

Last Answer : A : Terminates at local optimum & Does not find optimum solution

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 D : Fail to find a solution

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 D : Fail to find a solution

Last Answer : A : Terminates at local optimum & Does not find optimum solution

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 D : Fail to find a solution

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 D : Fail to find a solution

Last Answer : A : Terminates at local optimum & Does not find optimum solution

When will Hill-Climbing algorithm terminate? A : Stopping criterion met B : Global Min/Max is achieved C : No neighbour has higher value D : no criteria to terminate

Description : When will Hill-Climbing algorithm terminate? A : Stopping criterion met B : Global Min/Max is achieved C : No neighbour has higher value D : no criteria to terminate

Last Answer : C : No neighbour has higher value

What is the other name for forward state-space search? a) Progression planning b) Regression planning c) Test planning d) None of the mentioned

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

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 recursion proceeds all the way down to the leaves of the tree, and then the minimax values are backed up through the tree as the recursion unwinds. 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

Last Answer : a) True

Sussman Anomaly illustrates a weakness of interleaved planning algorithm. a) True b) False

Description : Sussman Anomaly illustrates a weakness of interleaved planning algorithm. a) True b) False

Last Answer : b) False

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

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

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 called chronological-backtracking. It is also possible to go all the way to set of variable that caused failure. a) True b) False

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

Last Answer : a) True

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 : 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

Last Answer : a) True

A complete, local search algorithm always finds goal if one exists, an optimal algorithm always finds a global minimum/maximum. a) True b) False

Description : A complete, local search algorithm always finds goal if one exists, an optimal algorithm always finds a global minimum/maximum. a) True b) False

Last Answer : a) True

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

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

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

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

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

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

What will backward chaining algorithm will return? a) Additional statements b) Substitutes matching the query c) Logical statement d) All of the mentioned

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