AI Test

The main task of a problem-solving agent is a) Solve the given problem and reach to goal b) To find out which sequence of action will get it to the goal state c) All of the mentioned d) None of the mentioned

All of the mentioned

To which depth does the alpha-beta pruning can be applied? a) 10 states b) 8 States c) 6 States d) Any depth

Any depth

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

Best-First-Search

Which search is implemented with an empty first-in-first-out queue? a) Depth-first search b) Breadth-first search c) Bidirectional search d) None of the mentioned

Breadth-first search

An Artificial Neural Network Is based on a) Strong Artificial Intelligence approach b) Weak Artificial Intelligence approach c) Cognitive Artificial Intelligence approach d) Applied Artificial Intelligence approach

Cognitive Artificial Intelligence approach

What is meant by agent's percept sequence? a) Used to perceive the environment b) Complete history of actuator c) Complete history of perceived things d) None of the mentioned

Complete history of perceived things

What is the rule of simple reflex agent? a) Simple-action rule b) Condition-action rule c) Simple & Condition-action rule d) None of the mentioned

Condition-action rule

Which is used to provide the feedback to the learning element? a) Critic b) Actuators c) Sensor d) None of the mentioned

Critic

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

Deepest

Which search method takes less memory? a) Depth-First Search b) Breadth-First search c) Linear Search d) Optimal search

Depth-First Search

Which search implements stack operation for searching the states? a) Depth-limited search b) Depth-first search c) Breadth-first search d) None of the mentioned

Depth-first search

Zero sum games are the one in which there are two agents whose actions must alternate and in which the utility values at the end of the game are always the same. a) True b) False

False

Categorize Crossword puzzle in Fully Observable / Partially Observable. a) Fully Observable b) partially Observable c) All of the mentioned d) None of the mentioned

Fully Observable

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

Greedy local 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

Heuristic approach (Some knowledge is stored)

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

Heuristic 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

Hill-Climbing

Which search uses the problem specific knowledge beyond the definition of the problem? a) Informed search b) Depth-first search c) Breadth-first search d) Uninformed search

Informed search

A problem in a search space is defined by one of these state. a) Initial state b) Last state c) Intermediate state d) All of the above

Initial state

The performance of an agent can be improved by? a) Learning b) Observing c) Perceiving d) None of the mentioned

Learning

Which is used to improve the agents performance? a) Perceiving b) Learning c) Observing d) None of the mentioned

Learning

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.) a) O(bd+1) and O(bd+1) b) O(b2) and O(d2) c) O(d2) and O(b2) d) O(d2) and O(d2)

O(bd+1) and O(bd+1)

What is the space complexity of Depth-first search? a) O(b) b) O(bl) c) O(m) d) O(bm)

O(bm)

What is the space complexity of Greedy search? a) O(b) b) O(bl) c) O(m) d) O(bm)

O(bm)

What kind of environment is crossword puzzle? a) Static b) Dynamic c) Semi Dynamic d) None of the mentioned

Static

A completely automated chess engine (Learn from previous games) is based on a) Strong Artificial Intelligence approach b) Weak Artificial Intelligence approach c) Cognitive Artificial Intelligence approach d) Applied Artificial Intelligence approach

Strong Artificial Intelligence approach

The _______ is a touring problem in which each city must be visited exactly once. The aim is to find the shortest tour. a) Finding shortest path between a source and a destination b) Travelling Salesman problem c) Map coloring problem d) Depth first search traversal on a given map represented as a graph

Travelling Salesman problem

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

Tree algorithm

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

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

True

Blind searching is general term for a) Informed Search b) Uninformed Search c) Informed & Unformed Search d) Heuristic Search

Uninformed Search

What is the heuristic function of greedy best-first search? a) f(n) != h(n) b) f(n) < h(n) c) f(n) = h(n) d) f(n) > h(n)

f(n) = h(n)

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

A* search

Hill-Climbing approach stuck for the following reasons a) Local maxima b) Ridges c) Plateaux d) All of the mentioned

All of the mentioned

The Task Environment of an agent consists of a) Sensors b) Actuators c) Performance Measures d) All of the mentioned

All of the mentioned

What among the following is/are the example of the intelligent agent/agents? ) Human b) Robot c) Autonomous Spacecraft d) All of the mentioned

All of the mentioned

What could possibly be the environment of a Satellite Image Analysis System? a) Computers in space and earth b) Image categorization techniques c) Statistical data on image pixel intensity value and histograms d) All of the mentioned

All of the mentioned

What is rational at any given time depends on a) The performance measure that defines the criterion of success b) The agent's prior knowledge of the environment c) The actions that the agent can perform d) All of the mentioned

All of the mentioned

Which of the following is/are Uninformed Search technique/techniques a) Breadth First Search (BFS) b) Depth First Search (DFS) c) Bidirectional Search d) All of the mentioned

All of the mentioned

Where does the values of alpha-beta search get updated? a) Along the path of search b) Initial state itself c) At the end d) None of the mentioned

Along the path of search

Which search is equal to minimax search but eliminates the branches that can't influence the final decision? a) Depth-first search b) Breadth-first search c) Alpha-beta pruning d) None of the mentioned

Alpha-beta pruning

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

Depth-first search

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

Depth-limited search

The action of the Simple reflex agent completely depends upon a) Perception history b) Current perception c) Learning theory d) Utility functions

Current perception

Though local search algorithms are not systematic, key advantages would include a) Less memory b) More time c) Finds a solution in large infinite space d) Less memory & Finds a solution in large infinite space

Less memory & Finds a solution in large infinite space

In many problems the path to goal is irrelevant, this class of problems can be solved using, a) Informed Search Techniques b) Uninformed Search Techniques c) Local Search Techniques d) Informed & Uninformed Search Techniques

Local Search Techniques

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

Lowest path cost

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

MIN/MAX Algorithms

What is Artificial intelligence? a) Putting your intelligence into Computer b) Programming with your own intelligence c) Making a Machine intelligent d) Playing a Game

Making a Machine intelligent

Zero sum game has to be a ______ game. a) Single player b) Two player c) Multiplayer d) Three player

Multiplayer

Hill-Climbing algorithm terminates when, a) Stopping criterion met b) Global Min/Max is achieved c) No neighbor has higher value d) All of the mentioned

No neighbor has higher value

Which is not the commonly used programming language for AI? a) Python b) Java c) LISP d) PHP

PHP

Which instruments are used for perceiving and acting upon the environment? a) Sensors and Actuators b) Sensors c) Perceiver d) None of the mentioned

Sensors and Actuators

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

Shallowest

The process of removing detail from a given state representation is called______ a) Extraction b) Abstraction c) Information Retrieval d) Mining of data

Abstraction

A game can be formally defined as a kind of search problem with the following components: a) Initial State b) Successor Function c) Terminal Test d) All of the mentioned

All of the mentioned

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

All of the mentioned

A problem solving approach works well for a) 8-Puzzle problem b) 8-queen problem c) Finding an optimal path from a given source to a destination d) Mars Hover (Robot Navigation) e) All of the mentioned

All of the mentioned

An 'agent' is anything that, a) Perceives its environment through sensors and acting upon that environment through actuators b) Takes input from the surroundings and uses its intelligence and performs the desired operations c) A embedded program controlling line following robot d) All of the mentioned

All of the mentioned

Artificial Intelligence has its expansion in the following application. (Mark all that apply) a) Planning and Scheduling b) Game Playing c) Diagnosis d) All of the mentioned

All of the mentioned

Following could be the approaches to Artificial Intelligence a) Strong Artificial Intelligence b) Weak Artificial Intelligence c) Applied Artificial Intelligence d) All of the mentioned

All of the mentioned

Which function will select the lowest expansion node at first for evaluation? a) Greedy best-first search b) Best-first search c) Depth-first search d) None of the mentioned

Best-first search

Which value is assigned to alpha and beta in the alpha-beta pruning? a) Alpha = max b) Beta = min c) Beta = max d) Both Alpha = max & Beta = min

Both Alpha = max & Beta = min

What kind of observing environments are present in artificial intelligence? a) Partial b) Fully c) Learning d) Both Partial & Fully

Both Partial & Fully

What are the composition for agents in artificial intelligence? a) Program b) Architecture c) Both Program & Architecture d) None of the mentioned

Both Program & Architecture

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

Estimated cost of cheapest path from root to goal node

Best-First search is a type of informed search, which uses ________________ to choose the best next node for expansion. a) Evaluation function returning lowest evaluation b) Evaluation function returning highest evaluation c) Evaluation function returning lowest & highest evaluation d) None of them is applicable

Evaluation function returning lowest evaluation

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. a) True b) False

False

In greedy approach evaluation function is 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

Heuristic function

In which agent does the problem generator is present? a) Learning agent b) Observing agent c) Reflex agent d) None of the mentioned

Learning agent

In A* approach evaluation function is 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

Path cost from start node to current node + Heuristic cost

Best-First search can be implemented using the following data structure. a) Queue b) Stack c) Priority Queue d) Circular Queue

Priority Queue

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

Problem, solution

Which values are independent in minimax search algorithm? a) Pruned leaves x and y b) Every states are dependent c) Root is independent d) None of the mentioned

Pruned leaves x and y

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

Quality of heuristic function

Which data structure conveniently used to implement BFS? a) Stacks b) Queues c) Priority Queues d) All of the mentioned

Queues

What is state space? a) The whole problem b) Your Definition to a problem c) Problem you design d) Representing your problem with variable and parameter

Representing your problem with variable and parameter

The complexity of minimax algorithm is a) Same as of DFS b) Space - bm and time - bm c) Time - bm and space - bm d) Same as BFS

Same as of DFS

LIFO is ______ where as FIFO is ________ a) Stack, Queue b) Queue, Stack c) Priority Queue, Stack d) Stack. Priority Queue

Stack, Queue

Which data structure conveniently used to implement DFS? a) Stacks b) Queues c) Priority Queues d) All of the mentioned

Stacks

One of the main cons of hill-climbing search is, 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

Terminates at local optimum & Does not find optimum solution

Greedy search strategy chooses the node for expansion a) Shallowest b) Deepest c) The one closest to the goal node d) Minimum heuristic cost

The one closest to the goal node

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

True

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. State whether true or false. a) True b) False

True

An omniscient agent knows the actual outcome of its actions and can act accordingly; but omniscience is impossible in reality. Rational Agent always does the right thing; but Rationality is possible in reality. State true or false a) True b) False

True

Performance Measures are fixed for all agents. State true or false a) True b) False

True

Rational agent is the one who always does the right thing. State true or false a) True b) False

True

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

True

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

True

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. a) True b) False

True

Which search strategy is also called as blind search? a) Uninformed search b) Informed search c) Simple reflex search d) All of the mentioned

Uninformed search

Optimality of BFS is a) When there is less number of nodes b) When all step costs are equal c) When all step costs are unequal d) None of the mentioned

When all step costs are equal

When is breadth-first search is optimal? a) When there is less number of nodes b) When all step costs are equal c) When all step costs are unequal d) None of the mentioned

When all step costs are equal