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

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
by

1 Answer

Answer :

c) The one closest to the goal node
by

Related questions

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

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

Which search method will expand the node that is closest to the goal? a) Best-first search b) Greedy best-first search c) A* search d) None of the mentioned

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Breadth-first search always expands the ______ node in the current fringe of the search tree. a) Shallowest b) Child node c) Deepest

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Last Answer : a) Shallowest

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

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Last Answer : d) All of the mentioned

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Last Answer : a) Lowest path cost

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Last Answer : (C) Greedy best first search algorithm

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Last Answer : A : Heuristic function

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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

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Last Answer : b) Heuristic search

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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 (D) Only (a), (b) and (c).

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Last Answer : (D) Only (a), (b) and (c).

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Last Answer : c) Path cost from start node to current node + Heuristic cost

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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 goal. All we can do is choose the node that appears to be best according to the evaluation function. a) True b) False

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Last Answer : a) True

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

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Last Answer : a) True

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

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Last Answer : a) True

What among the following could the universal instantiation of ___________ For all x King(x) ^ Greedy(x) => Evil(x) a) King(John) ^ Greedy(John) => Evil(John) b) King(y) ^ Greedy(y) => Evil(y) c) King(Richard) ^ Greedy(Richard) => Evil(Richard) d) All of the mentioned

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Last Answer : d) All of the mentioned

what is heuristic function A : Lowest path cost B : Cheapest path from root to goal node C : Average path cost D : Estimated cost of cheapest path from root to goal node

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Last Answer : D : Estimated cost of cheapest path from root to goal node

what is heuristic function A : Lowest path cost B : Cheapest path from root to goal node C : Average path cost D : Estimated cost of cheapest path from root to goal node

Description : what is heuristic function A : Lowest path cost B : Cheapest path from root to goal node C : Average path cost D : Estimated cost of cheapest path from root to goal node

Last Answer : D : Estimated cost of cheapest path from root to goal node

what is heuristic function A : Lowest path cost B : Cheapest path from root to goal node C : Average path cost D : Estimated cost of cheapest path from root to goal node

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Last Answer : D : Estimated cost of cheapest path from root to goal node

what is heuristic function A : Lowest path cost B : Cheapest path from root to goal node C : Average path cost D : Estimated cost of cheapest path from root to goal node

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Last Answer : D : Estimated cost of cheapest path from root to goal node

What is the meaning for greedy local search?

Description : What is the meaning for greedy local search?

Last Answer :  It goals (picks) a good neighbor state without thinking ahead about where to go next. 

Define Greedy Best First Search.

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).

Which is used to improve the performance of heuristic search? a) Quality of nodes b) Quality of heuristic function c) Simple form of nodes d) None of the mentioned

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Last Answer : b) Quality of heuristic function

What is the general term of Blind searching? a) Informed Search b) Uninformed Search c) Informed & Unformed Search d) Heuristic Search

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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

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Last Answer : D . All of the above

The ____ level contains constituents at the third level which are knowledge based system, heuristic search, automatic theorem proving, multi-agent system. A. Cognition level B. Gross level C. Functional level D. All of above

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Last Answer : B. Gross level 

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

Merge sort uses a) Divide-and-conquer b) Backtracking c) Heuristic approach d) Greedy approach

Description : Merge sort uses a) Divide-and-conquer b) Backtracking c) Heuristic approach d) Greedy approach

Last Answer : a) Divide-and-conquer

Define search node.

Description : Define search node.

Last Answer : The root of the search tree that is the initial state of the problem is called search node. 

Which of the following search strategy uses a problem specific knowledge A : uninformed Search B : Breadth-First-Search C : Heuristic Search D : Best search

Description : Which of the following search strategy uses a problem specific knowledge A : uninformed Search B : Breadth-First-Search C : Heuristic Search D : Best search

Last Answer : C : Heuristic Search

Which of the following search strategy uses a problem specificknowledge A : uninformed Search B : Breadth-First-Search C : Heuristic Search D : Best search

Description : Which of the following search strategy uses a problem specificknowledge A : uninformed Search B : Breadth-First-Search C : Heuristic Search D : Best search

Last Answer : C : Heuristic Search

Which of the following search strategy uses a problem specific knowledge A : uninformed Search B : Breadth-First-Search C : Heuristic Search D : Best search

Description : Which of the following search strategy uses a problem specific knowledge A : uninformed Search B : Breadth-First-Search C : Heuristic Search D : Best search

Last Answer : C : Heuristic Search

A ____ is a rule of thumb, strategy, trick, simplification, or any other kind of device which drastically limits search for solutions in large problem spaces. A. Heuristic B. Critical C. Value based D. Analytical

Description : A ____ is a rule of thumb, strategy, trick, simplification, or any other kind of device which drastically limits search for solutions in large problem spaces. A. Heuristic B. Critical C. Value based D. Analytical

Last Answer : A. Heuristic

Forward chaining systems are _____________ where as backward chaining systems are ___________ a) Goal-driven, goal-driven b) Goal-driven, data-driven c) Data-driven, goal-driven d) Data-driven, data-driven

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Last Answer : c) Data-driven, goal-driven

Searching using query on Internet is, use of ___________ type of agent. a) Offline agent b) Online agent c) Both Offline & Online agent d) Goal Based & Online agent

Description : Searching using query on Internet is, use of ___________ type of agent. a) Offline agent b) Online agent c) Both Offline & Online agent d) Goal Based & Online agent

Last Answer : d) Goal Based & Online agent

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

__________ 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 action sequences are used to achieve the agent’s goal? a) Search b) Plan c) Retrieve d) Both Search & Plan

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Last Answer : d) Both Search & Plan