Artificial Intellegence and R MCQ\'s and short notes PDF

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Get benifited wih Artificial Intellegence and R MCQ's and short notes for the online examination of Savitribai Phule Pune University...

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This sheet is for 1 Mark questions S.r No e.g 1

Question Write down question

Image

a

img.jpg Option a

b

c

Option b Option c PostLevel-order order Traversal Traversal

1

Depth First Search is equivalent to which of the traversal in the Binary Trees?

Pre-order Traversal

2

Time Complexity of DFS is? (V – number of vertices, E – number of edges)

O(E)

O(V)

O(V+E)

Linked List

Tree

Graph with back edges

C*

A*

E*

data structure

type of tree

sorting algorithm

stack

queue

array

stack

queue

array

The Depth First Search traversal of a graph will result into? Which algorithm is used in graph traversal 4 and path finding? 3

5 Branch and bound is a __________ Which data structure is used for 6 implementing a LIFO branch and bound strategy? Which data structure is used for 7 implementing a FIFO branch and bound strategy 8

Which of the following can traverse the state space tree only in DFS manner?

dynamic branch and program bound ming

9

Which of the following is false in the case of a spanning tree of a graph G?

It is tree that spans G

Consider a undirected graph G with vertices { A, B, C, D, E}. In graph G, every edge has distinct weight. Edge CD is edge 10 with minimum weight and edge AB is edge with maximum weight. Then, which of the following is false?

11

Which search strategy is also called as blind search?

greedy algorithm

It is a It can be subgraph either cyclic of the G or acyclic

If AB is in a Every minimum minimum spanning No minimum spanning tree, then spanning tree tree of G its contains AB must removal contain CD must disconnec tG Uninformed Informed Simple reflex search search search

12

Which search is implemented with an empty first-in-first-out queue?

BreadthDepth-first first search search

13

How many successors are generated in backtracking search?

1

Which algorithm is used to solve any kind 14 of problem?

15

Which search algorithm imposes a fixed depth limit on nodes?

16

Which search implements stack operation for searching the states?

Strategies that know whether one non17 goal state is “more promising” than another are called ___________

Bidirectional search 2

3

Breadthfirst algorithm

Bidirectional Tree search algorithm algorithm

Depthlimited search Depthlimited search

Depthfirst search Depthfirst search

Iterative deepening search Iterative deepening search

Informed & Heuristic & Unformed Unformed Unformed Search Search Search

18

uniform-cost search expands the node n with the __________

Lowest path cost

Heuristic Highest path cost cost

19

What is the other name of informed search strategy?

Simple search

Heuristic Online search search

Which search uses the problem specific 20 knowledge beyond the definition of the problem?

Informed search

Depthfirst search

21 A heuristic is a way of trying ___________

To search and To discover measure something how far a or an idea node in a embedded search tree in a seems to program be from a goal

To compare two nodes in a search tree to see if one is better than another

22 A* algorithm is based on ___________

DepthBreadthFirst First-Search –Search

Best-FirstSearch

Breadth-first search

Best-First search is a type of informed 23 search, which uses ________________ to choose the best next node for expansion

24 Heuristic function h(n) is ________

25

26

27

Greedy search strategy chooses the node for expansion in ___________

What is the evaluation function in greedy approach?

What is the evaluation function in A* approach?

In many problems the path to goal is 28 irrelevant, this class of problems can be solved using ____________

Evaluation function returning lowest evaluation

Evaluation function returning highest evaluatio n

Evaluation function returning lowest & highest evaluation

Lowest path cost

Cheapest path from root to goal node

Estimated cost of cheapest path from root to goal node

Shallowest Deepest

The one closest to the goal node

Heuristic function

Path cost from start node to current node

Path cost from start node to current node + Heuristic cost

Heuristic function

Path cost from start node to current node

Path cost from start node to current node + Heuristic cost

Uninform Informed ed Search Local Search Search Techniqu Techniques Techniques es

Finds a solution in large infinite space

Though local search algorithms are not 29 systematic, key advantages would include __________

Less memory

More time

_______________ Is an algorithm, a loop 30 that continually moves in the direction of increasing value – that is uphill.

Up-Hill Search

HillHill algorithm Climbing

When will Hill-Climbing algorithm 31 terminate?

Stopping criterion met

Global No neighbor Min/Max has higher is value achieved

Hill climbing sometimes called ____________ because it grabs a good 32 neighbor state without thinking ahead about where to go next

Heuristic Needy local Greedy local local search search search

Searching using query on Internet is, use of 33 ___________ type of agent

Offline agent

Online agent

Both Offline & Online agent Priority Queue

34

Best-First search can be implemented using the following data structure

Queue

Stack

35

Which is used to improve the performance of heuristic search?

Quality of nodes

Quality of Simple form heuristic of nodes function

36

Which search is complete and optimal when h(n) is consistent?

Best-first search

Depthfirst search

Both Bestfirst & Depthfirst search

37

Which method is used to search better by learning?

Best-first search

Depthfirst search

Metalevel state space

38

Which search uses only the linear space for searching?

Best-first search

Recursive Depth-first best-first search search

39

What is the heuristic function of greedy best-first search?

f(n) != h(n)

f(n) < h(n) f(n) = h(n)

40

Which function will select the lowest expansion node at first for evaluation?

Greedy best- Best-first Depth-first first search search search

Correct Answer a/b/c/d

d Option d In-order a Traversal O(V*E)

c

Array

b

D*

b

problem d solving technique linked list a

linked list b backtracki d ng It includes every c vertex of the G

G has a unique minimum c spanning tree

All of the mentione a d

None of the b mentione d 4a None of the b mentione d Bidirectio a nal search Bidirectio b nal search Informed & d Heuristic Search Average a path cost None of the b mentione d Uninform a ed search

All of the mentione d d

Hill climbing

c

None of a them is applicable

Average c path cost

Minimum heuristic c cost Average of Path cost from start node to a current node and Heuristic cost

Average of Path cost from start node to c current node and Heuristic cost Informed & Uninform c ed Search Techniqu es

Less memory & Finds a solution d in large infinite space ReverseDown-Hill b search All of the mentione c d Optimal local search

c

Goal Based & d Online agent Circular c Queue None of the b mentione d A* search d None of the c mentione d None of the b mentione d f(n) > h(n) c None of the b mentione d

This sheet is for 1 Mark questions S.r No e.g 1

Question Write down question This set of Basic Artificial Intelligence Questions and Answers focuses on 1 “Constraints Satisfaction Problems”. 2 Which of the Following problems can be modeled as CSP?

Image img.jpg

3 What among the following constitutes to the incremental formulation of CSP? 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 4 assign. To overcome the need to backtrack in constraint satisfaction problem can be 5 eliminated by ____________ 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 chronologicalbacktracking. It is also possible to go all the way to set of variable that caused 6 failure Consider a problem of preparing a schedule for a class of student. What type of problem is this? 7 Constraint satisfaction problems on finite domains are typically solved using a 8 form of ___________ Solving a constraint satisfaction problem on a finite domain is an/a 9 ___________ problem with respect to the domain size. ____________ is/are useful when the original formulation of a problem is altered in some way, typically because the set of constraints to consider 10 evolves because of the environment. 11 Flexible CSPs relax on _______ 12 Language/Languages used for programming Constraint Programming includes ___________ 13 Backtracking is based on ____________ 14 Constraint Propagation technique actually modifies the CSP problem. 15 When do we call the states are safely explored? 16 Which of the following algorithm is generally used CSP search algorithm 17 Which of the following algorithm is generally used CSP search algorithm? 18 When do we call the states are safely explored? 19 Constraint Propagation technique actually modifies the CSP problem. 20 CSPs are – 21 A constraint is 22 A Binary CSP is 23 A CSP with only soft constraints, also called preferences 24 Searching using query on Internet is, use of ___________ type of agent 25 Mark two main features of Genetic Algorithm 26 Optimality of BFS is 27 A production rule consists of 28 The major component/components for measuring the performance of problem solving

29 30 31 32 33 34 35 36 37 38 39 40

Web Crawler is a/an What is state space? he main task of a problem-solving agent is The process by which the brain orders actions needed to complete a specific task is referred The famous spare tire problem or Scheduling classes for bunch of students or Air cargo tran To eliminate the inaccuracy problem in planning problem or partial order planning problem Planning graphs consists of ____________ Planning graphs works only for prepositional planning problems. _____________ algorithms is used to extract the plan directly from the planning graph, rath What is the other name of each plan resulted in partial order planning? . What are the two major aspects which combines AI Planning problem? Which of the following are action langauges

a Option a

b Option b

c Option c

d Option d

Correct Answer a/b/c/d

a) Constraints Satisfaction P b) Uninformed Search c) Local Search Pr d) All of the ment a a) 8-Puzzle problem b) 8-Queen problem c) Map coloring p d) All of the ment d d) All of the ment a) Path cost b) Goal cost c) Successor funct d

c) Hill algorithm d) Reverse-Down b

a) Forward search

b) Backtrack search

a) Forward Searching

b) Constraint Propaga c) Backtrack afterd) Omitting the coa

a) True

b) False

a) Search Problem a) Search Algorithms

a) P complete

a

b) Backtrack Problem

c) CSP

d) Planning Problem

b) Heuristic Search

d) All of the c) Greedy Search mentioned

b) NP complete

c) NP hard

c

d b

d) Domain depen

a) Static CSPs b) Dynamic CSPs c) Flexible CSPs d) None of the meb a a) Constraints b) Current State c) Initial State d) Goal State a a) Prolog b) C# c) C d) Fortrun a) Last in first out b) First in first out c) Recursion d) Both Last in firsd a) True b) False a a) A goal state is unreachabl b) A goal state is deni c) A goal state is rd) None of the mec a) Breadth-first search algor b) Depth-first search ac) Hill-climbing sed) None of the meb 1.Breadth-first search algor 2. Depth-first search a3. Hill-climbing se4. None of the meb 1. A goal state is unreachabl 2. A goal state is denie3. A goal state is r4. None of the mec a) True b) False a an alternative formulation f ways of formulating p problems that co problems that ari a something that prevents an a restriction on what a limitation of thenone of the aboveb a CSP with only two variablea CSP where each var a CSP with only twa CSP where the sd has only solutions with all comay have not any solucan have more thnone of the abovec 1. Offline agent 2. Online agent 3. Both Offline & 4. Goal Based & Od 1. Fitness function & Crosso 2. Crossover techniqu 3. Individuals amo4. Random mutat a 1. When there is less numbe2. When all step costs 3. When all step c4. None of the meb 1. A set of Rule 2. A sequence of step 3. Set of Rule & se4. Arbitrary repre c 1. Completeness 2. Optimality 3. Time and Space4. All of the ment d

1. Intelligent goal-based age2. Problem-solving ag 3. Simple reflex a 4. Model based a a 1. The whole problem 2. Your Definition to a3. Problem you d 4. Representing y d 1. Solve the given problem a2. To find out which s 3. All of the ment 4. None of the mec a) Planning problem b) Partial order planni c) Total order pla d) Both Planning pd a) Planning problem b) Partial Order plann c) Total order pla d) None of the mea a) Stacks b) Queue c) BST (Binary Sead) Planning Graphd a) a sequence of levels b) a sequence of level c) a sequence of ad) none of the meb a) True b) False a a) BFS/DFS b) A* c) Graph-Plan d) Greedy c a) Polarization b) Linearization c) Solarization d) None of the meb a) Search & Logic b) Logic & Knowledge c) FOL & Logic d) Knowledge Basa a) STRIP b)ADL C) All of the mentd) None of the mec

S.r No

This sheet is for 1 Mark questions Question

Image

a

1

Knowledge and reasoning also play a crucial role in dealing with __________________ environment.

Completely Observable

2

Treatment chosen by doctor for a patient for a disease is based on _____________

Only current symptoms

3

A knowledge-based agent can combine general knowledge with current percepts to infer hidden aspects of the current state prior to selecting actions.

4

A) Knowledge base (KB) is consists of set of statements. B) Inference is deriving a new sentence from the KB. Choose the correct option.

A is true, B is true

5

Wumpus World is a classic problem, best example of _______

Single player Game

6

True, true

7

‘α |= β ‘(to mean that the sentence α entails the sentence β) if and only if, in every model in which α is _____ β is also _____ Which is not a property of representation of knowledge?

8 9

Which is not Familiar Connectives in First Order Logic? Inference algorithm is complete only if _____________

10

An inference algorithm that derives only entailed sentences is called sound or truth-preserving.

11

Which algorithm will work backward from the goal to solve a problem?

Forward chaining

12

Which is mainly used for automated reasoning?

Backward chaining

13

What will backward chaining algorithm will return?

Additional statements

14

How can be the goal is thought of in backward chaining algorithm?

Queue

15

What is used in backward chaining algorithm?

Conjuncts

TRUE

Representational Verification

and It can derive any sentence

TRUE

16

Which algorithm are in more similar to backward chaining algorithm?

Depth-first search algorithm

17

Which problem can frequently occur in backward chaining algorithm?

Repeated states

18

How the logic programming can be constructed?

Variables

19

What form of negation does the prolog allows?

Negation as failure

20

Which is omitted in prolog unification algorithm?

Variable check

21

What is the frame?

A way of representing knowledge

22

Frames in artificial intelligence is derived from semantic nets.

WAHR

23

Which of the following elements constitutes the frame structure? Like semantic networks, frames can be queried using spreading activation. What is Hyponymy relation?

24 25

Facts or Data WAHR A is part of B

The basic inference mechanism in semantic network in which knowledge is represented as Frames is to follow the links between the nodes. There exists two way to infer using semantic networks in which knowledge is represented as Frames.

WAHR

28

What among the following constitutes the representation of the knowledge in different forms?

Relational method where each fact is set out systematically in columns

29

What are Semantic Networks?

30

Graph used to represent semantic network is _____________

A way of representing knowledge Undirected graph

31

Meronymy

32

Which of the following are the Semantic Relations used in Semantic Networks? What is Meronymy relation?

33

What is Hypernym relation?

A is part of B

34

What is Holonymy relation?

A is part of B

35

The basic inference mechanism in semantic network is to follow the links between the nodes.

WAHR

26 27

Intersection Search

A is part of B

The rule of Universal Instantiation (UI for short) says that we can infer any sentence obtained by substituting a ground term (a term without variables) for the variable. The corresponding Existential Instantiation rule: for the existential quantifier is slightly more complicated. For any sentence a, variable v, and constant symbol k that does not appear elsewhere in the knowledge base. Lifted inference rules require finding substitutions that make different logical expressions looks identical.

W...