Define Heuristic function, h (n).

Define Heuristic function, h (n).
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Answer :

 h (n) is defined as the estimated cost of the cheapest path from node n to a goal node. 
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Related questions

Define Admissible heuristic h (n).

Description : Define Admissible heuristic h (n).

Last Answer : In A* search, if it is optimal then, h(n) is an admissible heuristic which means h(n) never overestimates the cost to reach the goal.

Heuristic function h(n) is ________ a) Lowest path cost b) Cheapest path from root to goal node c) Estimated cost of cheapest path from root to goal node d) Average path cost

Description : Heuristic function h(n) is ________ a) Lowest path cost b) Cheapest path from root to goal node c) Estimated cost of cheapest path from root to goal node d) Average path cost

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

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

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

uniform-cost search expands the node n with the __________ a) Lowest path cost b) Heuristic cost c) Highest path cost d) Average path cost

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

What is the evaluation function in A* approach? a) Heuristic function b) Path cost from start node to current node c) Path cost from start node to current node + Heuristic cost d) Average of Path cost from start node to current node and Heuristic cost

Description : What is the evaluation function in A* approach? a) Heuristic function b) Path cost from start node to current node c) Path cost from start node to current node + Heuristic cost d) Average of Path cost from start node to current node and Heuristic cost

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

What is the evaluation function in greedy approach? a) Heuristic function b) Path cost from start node to current node c) Path cost from start node to current node + Heuristic cost d) Average of Path cost from start node to current node and Heuristic cost

Description : What is the evaluation function in greedy approach? a) Heuristic function b) Path cost from start node to current node c) Path cost from start node to current node + Heuristic cost d) Average of Path cost from start node to current node and Heuristic cost

Last Answer : a) Heuristic function

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

Description : 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

Last Answer : b) Quality of heuristic function

Special programs that assist programmers are called ____________ a) heuristic processors b) symbolic programmers c) intelligent programming tools d) program recognizers

Description : Special programs that assist programmers are called ____________ a) heuristic processors b) symbolic programmers c) intelligent programming tools d) program recognizers

Last Answer : c) intelligent programming tools

_____________ 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 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

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

Constraint satisfaction problems on finite domains are typically solved using a form of ___________ a) Search Algorithms b) Heuristic Search Algorithms c) Greedy Search Algorithms d) All of the mentioned

Description : Constraint satisfaction problems on finite domains are typically solved using a form of ___________ a) Search Algorithms b) Heuristic Search Algorithms c) Greedy Search Algorithms d) All of the mentioned

Last Answer : d) All of the mentioned

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

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

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

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 : 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

Last Answer : d) All of the mentioned

What is the other name of informed search strategy? a) Simple search b) Heuristic search c) Online search d) None of the mentioned

Description : What is the other name of informed search strategy? a) Simple search b) Heuristic search c) Online search d) None of the mentioned

Last Answer : b) Heuristic search

Strategies that know whether one non-goal state is “more promising” than another are called ___________ a) Informed & Unformed Search b) Unformed Search c) Heuristic & Unformed Search d) Informed & Heuristic Search

Description : Strategies that know whether one non-goal state is “more promising” than another are called ___________ a) Informed & Unformed Search b) Unformed Search c) Heuristic & Unformed Search d) Informed & Heuristic Search

Last Answer : d) Informed & Heuristic Search

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

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

Last Answer : b) Uninformed Search

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

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)

Which method is effective for escaping from local minima? a) Updating heuristic estimate b) Reducing heuristic estimate c) Eliminating heuristic estimate d) None of the mentioned

Description : Which method is effective for escaping from local minima? a) Updating heuristic estimate b) Reducing heuristic estimate c) Eliminating heuristic estimate d) None of the mentioned

Last Answer : a) Updating heuristic estimate

What is the term used for describing the judgmental or commonsense part of problem solving? a) Heuristic b) Critical c) Value based d) Analytical

Description : What is the term used for describing the judgmental or commonsense part of problem solving? a) Heuristic b) Critical c) Value based d) Analytical

Last Answer : a) Heuristic

An Artificial Intelligence technique that allows computers to understand associations and relationships between objects and events is called _____________ a) heuristic processing b) cognitive science c) relative symbolism d) pattern matching

Description : An Artificial Intelligence technique that allows computers to understand associations and relationships between objects and events is called _____________ a) heuristic processing b) cognitive science c) relative symbolism d) pattern matching

Last Answer : c) relative symbolism

What are the two subfields of Natural language processing? a) symbolic and numeric b) time and motion c) algorithmic and heuristic d) understanding and generation

Description : What are the two subfields of Natural language processing? a) symbolic and numeric b) time and motion c) algorithmic and heuristic d) understanding and generation

Last Answer : c) algorithmic and heuristic

Which term is used for describing the judgmental or commonsense part of problem solving? a) Heuristic b) Critical c) Value based d) Analytical

Description : Which term is used for describing the judgmental or commonsense part of problem solving? a) Heuristic b) Critical c) Value based d) Analytical

Last Answer : a) Heuristic

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 : 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

Last Answer : d) All of the mentioned

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

An AI technique that allows computers to understand associations and relationships between objects and events is called: a. heuristic processing b. cognitive science c. relative symbolism d. pattern matching

Description : An AI technique that allows computers to understand associations and relationships between objects and events is called: a. heuristic processing b. cognitive science c. relative symbolism d. pattern matching

Last Answer : d. pattern matching

A bidirectional feedback loop links computer modelling with: a. artificial science b. heuristic processing c. human intelligence d. cognitive science

Description : A bidirectional feedback loop links computer modelling with: a. artificial science b. heuristic processing c. human intelligence d. cognitive science

Last Answer : d. cognitive science

What are the 2 types of memory bounded heuristic algorithms?

Description : What are the 2 types of memory bounded heuristic algorithms?

Last Answer : i. Recursive Best First Search(RBFS)  ii. Memory bounded A*(MA*)

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

Description : 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

Last Answer : B. Gross level 

______ do not guarantee optimal/any solutions A. Heuristic B. Critical C. Value based D. Analytical

Description : ______ do not guarantee optimal/any solutions A. Heuristic B. Critical C. Value based D. Analytical 

Last Answer : A. Heuristic 

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 

What is the term used for describing the judgmental or commonsense part of problem solving? A. Heuristic B. Critical C. Value based D. Analytical

Description : What is the term used for describing the judgmental or commonsense part of problem solving? A. Heuristic B. Critical C. Value based D. Analytical

Last Answer : A. Heuristic 

What is the term used for describing the judgmental or commonsense part of problem solving? A. Heuristic B. Critical C. Value based D. Analytical E. None of the above

Description : What is the term used for describing the judgmental or commonsense part of problem solving? A. Heuristic B. Critical C. Value based D. Analytical E. None of the above

Last Answer : A. Heuristic 

Define Evaluation function, f(n).

Description : Define Evaluation function, f(n).

Last Answer : A node with the lowest evaluation is selected for expansion, because evaluation measures distance to the goal.

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

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

A Term is either an individual constant (a 0-ary function), or a variable, or an n-ary function applied to n terms: F(t1 t2 ..tn). a) True b) False

Description : A Term is either an individual constant (a 0-ary function), or a variable, or an n-ary function applied to n terms: F(t1 t2 ..tn). a) True b) False

Last Answer : a) True

Define Successor function.

Description : Define Successor function.

Last Answer : A value can be assigned to any unassigned variable, provided that does not conflict with previously assigned variables.

Define Agent Function.

Description : Define Agent Function.

Last Answer : It is a mathematical description which deals with the agent’s behavior that maps the given percept sequence into an action.

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

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 the evaluation function in greedy approach? A : Heuristic function B : Path cost from start node to current node C : Path cost from start node to current node + Heuristic cost D : Average of Path cost from start node to current node and Heuristic cost

Description : What is the evaluation function in greedy approach? A : Heuristic function B : Path cost from start node to current node C : Path cost from start node to current node + Heuristic cost D : Average of Path cost from start node to current node and Heuristic cost

Last Answer : A : Heuristic function

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

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 the evaluation function in greedy approach? A : Heuristic function B : Path cost from start node to current node C : Path cost from start node to current node + Heuristic cost D : Average of Path cost from start node to current node and Heuristic cost

Description : What is the evaluation function in greedy approach? A : Heuristic function B : Path cost from start node to current node C : Path cost from start node to current node + Heuristic cost D : Average of Path cost from start node to current node and Heuristic cost

Last Answer : A : Heuristic function

The traveling salesman problem involves n cities with paths connecting the cities. The time taken for traversing through all the cities, without knowing in advance the length of a minimum tour, is ___________ a) O(n) b) O(n2) c) O(n!) d) O(n/2)

Description : The traveling salesman problem involves n cities with paths connecting the cities. The time taken for traversing through all the cities, without knowing in advance the length of a minimum tour, is ___________ a) O(n) b) O(n2) c) O(n!) d) O(n/2)

Last Answer : c) O(n!)

n(log n) is referred to A. A measure of the desired maximal complexity of data mining algorithms B. A database containing volatile data used for the daily operation of an organization C. Relational database management system D. None of these

Description : n(log n) is referred to A. A measure of the desired maximal complexity of data mining algorithms B. A database containing volatile data used for the daily operation of an organization C. Relational database management system D. None of these

Last Answer : A. A measure of the desired maximal complexity of data mining algorithms

The initial state and the legal moves for each side define the __________ for the game. a) Search Tree b) Game Tree c) State Space Search d) Forest

Description :  The initial state and the legal moves for each side define the __________ for the game. a) Search Tree b) Game Tree c) State Space Search d) Forest

Last Answer : b) Game Tree

Define Information Extraction.

Description : Define Information Extraction.

Last Answer : It is a process of creating database entries by skimming a text and looking for occurrences of a particular class of object.

Define Information Retrieval (IR).

Description : Define Information Retrieval (IR).

Last Answer :  IR is the task of finding documents that are relevant to user’s need for information.