Test1 Flashcards
Which search strategy is also called as blind search? Uninformed search Informed search Simple reflex search All of the mentioned
Uninformed search
How many main types are available in uninformed search method as our lectures? 3 4 5 6
5
Which search is implemented with an empty first-in-first-out queue? Depth-first search Breadth-first search Bidirectional search None of the mentioned
Breadth-first search
When is breadth-first search is optimal? When there is less number of nodes When all step costs are equal When all step costs are unequal None of the mentioned
When all step costs are equal
What is the space complexity of Depth-first search? O(b) O(bl) O(m) O(bm)
O(bm)
How many parts does a problem consists of? 1 2 3 4
4
Which algorithm is expected to solve any kind of problem? Breadth-first algorithm Tree algorithm Bidirectional search algorithm None of the mentioned
Tree algorithm
Which search algorithm imposes a fixed depth limit on nodes? Depth-limited search Depth-first search Iterative deepening search Bidirectional search
Depth-limited search
Which search implements stack operation for searching the states? Depth-limited search Depth-first search Breadth-first search None of the mentioned
Depth-first search
Blind searching is general term for Informed Search Uninformed Search Informed & Unformed Search Heuristic Search
Uninformed Search
Strategies that know whether one non-goal state is "more promising" than another are called Informed & Unformed Search Unformed Search Heuristic & Unformed Search Informed & Heuristic Search
Informed & Heuristic Search
Which of the following is/are Uninformed Search technique/techniques Breadth First Search (BFS) Depth First Search (DFS) Bidirectional Search All of the mentioned
All of the mentioned
Which data structure conveniently used to implement BFS? Stacks Queues Priority Queues All of the mentioned
Queues
Which data structure conveniently used to implement DFS? Stacks Queues Priority Queues All of the mentioned
Stacks
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.) O(bd+1) and O(bd+1) O(b2) and O(d2) O(d2) and O(b2) O(d2) and O(d2)
O(bd+1) and O(bd+1)
Breadth-first search is not optimal when all step costs are equal, because it always expands the shallowest unexpanded node. State whether true or false.
False
uniform-cost search expands the node n with the\_\_\_\_\_\_\_\_\_\_ Lowest path cost Heuristic cost Highest path cost Average path cost
Lowest path cost
Depth-first search always expands the \_\_\_\_\_\_ node in the current fringe of the search tree. Shallowest Child node Deepest Minimum cost
Deepest
Breadth-first search always expands the \_\_\_\_\_\_ node in the current fringe of the search tree. Shallowest Child node Deepest Minimum cost
Shallowest
Optimality of BFS is When there is less number of nodes When all step costs are equal When all step costs are unequal None of the mentioned
When all step costs are equal
We often regard a LIFO as a \_\_\_\_\_\_ and an FIFO as \_\_\_\_\_\_\_\_ Stack, Queue Queue, Stack Priority Queue, Stack Stack. Priority Queue
Stack, Queue
The main task of a problem-solving agent is
Solve the given problem and reach to goal
To find out which sequence of action will get it to the goal state
All of the mentioned
None of the mentioned
All of the mentioned
What is state space? The whole problem Your Definition to a problem Problem you design Representing your problem with variable and parameter
Representing your problem with variable and parameter
The problem-solving agent with several immediate options of unknown value can decide what to do by just examining different possible sequences of actions that lead to states of known value, and then choosing the best sequence. This process of looking for such a sequence is called Search. (True or False)
True
A search algorithm takes \_\_\_\_\_\_\_\_\_ as an input and returns \_\_\_\_\_\_\_\_ as an output. Input, output Problem, solution Solution, problem Parameters, sequence of actions
Problem, solution
A problem in a search space is defined by one of these state. Initial state Last state Intermediate state All of the above
Initial state
The Set of actions for a problem in a state space is formulated by a ___________
Intermediate states
Initial state
Successor function, which takes current action and returns next immediate state
None of the mentioned
Successor function, which takes current action and returns next immediate state
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. (True or false).
True
The process of removing detail from a given state representation is called\_\_\_\_\_\_ Extraction Abstraction Information Retrieval Mining of data
Abstraction
The _______ is a touring problem in which each city must be visited exactly once. The aim is to find the shortest tour.
8-Puzzle problem
8-queen problem
Finding an optimal path from a given source to a destination
Mars Hover (Robot Navigation)
Travelling Salesman problem
All of the mentioned
Travelling Salesman problem
Web Crawler is a/an Intelligent goal-based agent Problem-solving agent Simple reflex agent Model based agent
Intelligent goal-based agent
Which search method takes less memory? Depth-First Search Breadth-First search Linear Search Optimal search
Depth-First Search
Which is the best way to go for Game playing problem?
Linear approach
Heuristic approach (Some knowledge is stored)
Random approach
An Optimal approach
Heuristic approach (Some knowledge is stored)
What is the other name of informed search strategy? Simple search Heuristic search Online search None of the mentioned
Heuristic search
How many types of informed search method are in artificial intelligence? 1 2 3 4
4
Which search uses the problem specific knowledge beyond the definition of the problem? Informed search Depth-first search Breadth-first search Uninformed search
Informed search
Which function will select the lowest expansion node at first for evaluation? Greedy best-first search Best-first search Depth-first search None of the mentioned
Best-first search
What is the heuristic function of greedy best-first search? f(n) != h(n) f(n) < h(n) f(n) = h(n) f(n) > h(n)
f(n) = h(n)
Which search is complete and optimal when h(n) is consistent? Best-first search Depth-first search Both Best-first & Depth-first search A* search
A* search
Which is used to improve the performance of heuristic search? Quality of nodes Quality of heuristic function Simple form of nodes None of the mentioned
Quality of heuristic function
Which search method will expand the node that is closest/fastest to the goal? Best-first search Greedy best-first search A* search None of the mentioned
Greedy best-first search
A* algorithm is based on Breadth-First-Search Depth-First –Search Best-First-Search Hill climbing
Best-First-Search
Uninformed search strategies are better than informed search strategies.
(True/false)
False
Best-First search is a type of informed search, which uses ________________ to choose the best next node for expansion.
- Evaluation function returning lowest evaluation
- Evaluation function returning highest evaluation
- Evaluation function returning lowest & highest evaluation
- None of them is applicable
Evaluation function returning lowest evaluation
Best-First search can be implemented using the following data structure. Queue Stack Priority Queue Circular Queue
Priority Queue
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. State whether true or false.
True
Heuristic function h(n) is \_\_\_\_ Lowest path cost Cheapest path from root to goal node Estimated cost of cheapest path from root to goal node Average path cost
Estimated cost of cheapest path from root to goal node
Greedy search strategy chooses the node for expansion Shallowest Deepest The one closest to the goal node Minimum heuristic cost
The one closest to the goal node
In greedy approach evaluation function is
Heuristic function
Path cost from start node to current node
Path cost from start node to current node + Heuristic cost
Average of Path cost from start node to current node and Heuristic cost
Heuristic function
What is the space complexity of Greedy search? O(b) O(bl) O(m) O(bm)
O(bm)
In A* approach evaluation function is
- Heuristic function
- Path cost from start node to current node
- Path cost from start node to current node + Heuristic cost
- Average of Path cost from start node to current node and Heuristic cost
Path cost from start node to current node + Heuristic cost
A* is optimal if h(n) is an admissible heuristic-that is, provided that h(n) never underestimates the cost to reach the goal (True/false)
False
The _______ is a touring problem in which each city must be visited exactly once. The aim is to find the shortest tour
Finding shortest path between a source and a destination
Travelling Salesman problem
Map coloring problem
Depth first search traversal on a given map represented as a graph
Travelling Salesman problem
Which search uses only the linear space for searching? Best-first search Recursive best-first search Depth-first search None of the mentioned
None of the mentioned
The search strategy that uses a problem specific knowledge is known as
- Informed Search
- Best First Search
- Heuristic Search
- All of the mentioned
All of the mentioned
