Problem Solving – 1
1. 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) Both a) and b)
d) Neither a) nor b)
Answer: c
2. 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
e) A space where you know the solution
Answer: d
3.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. State True or False
a) True
b) False
Answer: a
4. 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
Answer: b
5. A problem in a search space Is defined by,
a) Initial state
b) Goal test
c) Intermediate states
d) All of the above
Answer: a, b
6. The Set of actions for a problem in a state space is
formulated by a ___________.
a) Intermediate states
b) Initial state
c) Successor function, which takes current action and
returns next immediate state
d) None of the mentioned
Answer: c
7. 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
Answer: a
8. The process of removing detail from a given state
representation is called______.
a) Extraction
b) Abstraction
c) Information Retrieval
d) Mining of data
Answer: b
9. A problem solving approach works well for
a) 8-Puzzle problem
b) 8-queen problem
c) Finding a optimal path from a given source to a
destination
d) Mars Hover (Robot Navigation)
Answer: d
10. 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
Answer: b
Problem Solving Approach – 2
1. Web Crawler is a/an
a) Intelligent goal-based agent
b) Problem-solving agent
c) Simple reflex agent
d) Model based agent
Answer: a, b
2. The major component/components for measuring the
performance of problem solving
a) Completeness
b) Optimality
c) Time and Space complexity
d) Correctness
Answer: a, b, c, d
3. A production rule consists of
a) A set of Rule
b) A sequence of steps
c) Both a) and b)
d) Arbitrary representation to problem
e) Directly getting solution
Answer: c
4. Which search method takes less memory?
a) Depth-First Search
b) Breadth-First search
c) Both (a) and (b)
d) Linear Search
e) Optimal search
Answer: a
5. 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
e) Stratified approach
Answer: b
6. The game of Poker is a single agent.
a) True
b) False
Answer: b
7. Satellite Image Analysis System is (Choose the one
that is not applicable).
a) Episodic
b) Semi-Static
c) Single agent
d) Partially Observable
Answer: d
8. What is the rule of simple reflex agent?
a) Simple-action rule
b) Condition-action rule
c) Both a & b
d) None of the mentioned
Answer: b
9. An agent is composed of,
a) Architecture
b) Agent Function
c) Perception Sequence
d) Architecture and Program
Answer: d
10. In which of the following agent does the problem
generator is present?
a) Learning agent
b) Observing agent
c) Reflex agent
d) None of the mentioned
Answer: a
Uninformed Search Strategy
1. Which search strategy is also called as blind search?
a) Uninformed search
b) Informed search
c) Simple reflex search
d) All of the mentioned
Answer:a
2. How many types are available in uninformed search
method?
a) 3
b) 4
c) 5
d) 6
Answer:c
3. Which search is implemented with an empty first-infirst-out queue?
a) Depth-first search
b) Breadth-first search
c) Bidirectional search
d) None of the mentioned
Answer:b
4. 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) Both a & c
Answer:b
5. How many successors are generated in backtracking
search?
a) 1
b) 2
c) 3
d) 4
Answer:a
6. What is the space complexity of Depth-first search?
a) O(b)
b) O(bl)
c) O(m)
d) O(bm)
Answer:d
7. How many parts does a problem consists of?
a) 1
b) 2
c) 3
d) 4
Answer:d
8. Which algorithm is used to solve any kind of problem?
a) Breath-first algorithm
b) Tree algorithm
c) Bidirectional search algorithm
d) None of the mentioned
Answer:b
9. 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
Answer:a
10. 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
Answer:b
Uninformed Search and Exploration – 1
1. Blind searching is general term for
a) Informed Search
b) Uninformed Search
c) Both a and b
d) Only a
Answer: b
2. Strategies that know whether one non-goal state is
“more promising” than another are called
a) Informed Search
b) Unformed Search
c) Heuristic Search
d) Blind Search
Answer: a, c
3. Which of the following is/are Uninformed Search
technique/techniques
a) Breath First Search (BFS)
b) Depth First Search (DFS)
c) Bi-directional Search
d) Best First Search
Answer: a, b, c
4. Which data structure conveniently used to implement
BFS?
a) Stacks
b) Queues
c) Priority Queues
d) Circular Queues
Answer: b, d
5. Which data structure conveniently used to implement
DFS?
a) Stacks
b) Queues
c) Priority Queues
d) All of the above
Answer: a
6. 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)
Answer: a
7. 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
Answer: b
8. uniform-cost search expands the node n with
the__________.
a) Lowest path cost
b) Heuristic cost
c) Highest path cost
d) Average path cost
Answer: a
9. 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
Answer: b, c
10. 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
Answer: a
Uninformed Search and Exploration – 2
1. 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) Both a & c
Answer: b
2. How many successors are generated in backtracking
search?
a) 1
b) 2
c) 3
d) 4
Answer: a
3. What is the space complexity of Depth-first search?
a) O(b)
b) O(bl)
c) O(m)
d) O(bm)
Answer: d
4. 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
Answer: a
5. LIFO is ______ where as FIFO is ________?
a) Stack, Queue
b) Queue, Stack
c) Priority Queue, Stack
d) Stack. Priority Queue
Answer: a
6. When the environment of an agent is partially
observable in search space following problem/problems
could occur.
a) Sensorless problems: If the agent has no sensors at all,
then (as far as it knows) it could be in one of several
possible initial states, and each action might therefore
lead to one of several possible successor states.
b) Contingency problems: If the environment is partially
observable or if actions are uncertain, then the agent’s
percepts provide new information after each action.
Each possible percept defines a contingency that must
be planned for. A problem is called adversarial if the
uncertainty is caused by the actions of another agent.
c) Exploration problems: When the states and actions of
the environment are unknown, the agent must act to
discover them. Exploration problems can be viewed as
an extreme case of contingency problems
d) All of the above
Answer: d
7. For general graph, how one can get rid of repeated
states?
a) By maintaining a list of visited vertices
b) By maintaining a list of traversed edges
c) By maintaining a list of non-visited vertices
d) By maintaining a list of non-traversed edges
Answer: a
8. DFS is ______ efficient and BFS is __________
efficient.
a) Space, Time
b) Time, Space
c) Time, Time
d) Space, Space
Answer: a
9. The main idea of bi-directional search is to reduce the
time complexity by searching two way simultaneously
from start node and another from goal node.
a) True
b) False
Answer: a
10. An algorithm is complete if
a) It terminates with a solution when one exists
b) It starts with a solution
c) It does not terminate with a solution
d) It has a loop
e) It has a decision parameter.
Answer: a
Informed Search Strategy
1. What is the other name of informed search strategy?
a) Simple search
b) Heuristic search
c) Online search
d) None of the mentioned
Answer:b
2. How many types of informed search method are in
artificial intelligence?
a) 1
b) 2
c) 3
d) 4
Answer:d
3. 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
Answer:a
4. Which function will select the lowest expansion node
atfirst for evaluation?
a) Greedy best-first search
b) Best-first search
c) Both a & b
d) None of the mentioned
Answer:b
5. 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)
Answer:c
6. Which search uses only the linear space for searching?
a) Best-first search
b) Recursive best-first search
c) Depth-first search
d) None of the mentioned
Answer:b
7. Which method is used to search better by learning?
a) Best-first search
b) Depth-first search
c) Metalevel state space
d) None of the mentioned
Answer:c
8. Which search is complete and optimal when h(n) is
consistent?
a) Best-first search
b) Depth-first search
c) Both a & b
d) A* search
Answer:d
9. 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
Answer:b
10. 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
Answer:b
Informed Search and Exploration – 1
1. 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) Only a) and b)
e) Only a), b) and c)
Answer: e
2. A* algorithm is based on
a) Breadth-First-Search
b) Depth-First –Search
c) Best-First-Search
d) Hill climbing
Answer: c
3. The search strategy the uses a problem specific
knowledge is known as
a) Informed Search
b) Uniform-Cost Search
c) Heuristic Search
d) Best First Search
Answer: a, c, d
4. Uninformed search strategies are better than
informed search strategies.
a) True
b) False
Answer: a
5. 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) Both a & b can be used
d) None of them is applicable
Answer: a
6. Best-First search can be implemented using the
following data structure.
a) Queue
b) Stack
c) Priority Queue
d) Circular Queue
Answer: c
7. 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
Answer: a
8. 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
Answer: c
9. Greedy search strategy chooses the node for
expansion
a) Shallowest
b) Deepest
c) The one closest to the goal node
d) Minimum heuristic cost
Answer: c
10. 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
Answer: a
Informed Search and Exploration – 2
1. 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) Both a & c
Answer: b
2. How many successors are generated in backtracking
search?
a) 1
b) 2
c) 3
d) 4
Answer: a
3. What is the space complexity of Greedy search?
a) O(b)
b) O(bl)
c) O(m)
d) O(bm)
Answer: d
4. 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
Answer: c
5. 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
6. What is the other name of informed search strategy?
a) Simple search
b) Heuristic search
c) Online search
d) None of the mentioned
Answer: b
7. 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)
Answer: c
8. Which search uses only the linear space for searching?
a) Best-first search
b) Recursive best-first search
c) Depth-first search
d) None of the mentioned
Answer: b
9. Which method is used to search better by learning?
a) Best-first search
b) Depth-first search
c) Metalevel state space
d) None of the mentioned
Answer: c
10. 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
Answer: b
Local Search Problems and Optimization Problems – 1
1. 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) Only a and b
Answer: c
2. 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) No optimum solution
Answer: a, c
3. 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
Answer: a
4. _______________ 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
Answer: b
5. Hill-Climbing algorithm terminates when,
a) Stopping criterion met
b) Global Min/Max is achieved
c) No neighbor has higher value
d) Local Min/Max is achieved
Answer: c, d
6. One of the main cons of hill-climbing search is,
a) Terminates at local optimum
b) Terminates at global optimum
c) Does not find optimum solution
d) Fail to find a solution
Answer: a, c
7. 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
Answer: a
8. 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
Answer: c
9. Hill-Climbing approach stuck for the following reasons
a) Local maxima
b) Ridges
c) Plateaux
d) All of above
Answer: d
10. ___________ algorithm keeps track of k states rather
than just one.
a) Hill-Climbing search
b) Local Beam search
c) Stochastic hill-climbing search
d) Random restart hill-climbing search
Answer: b
Local Search Problems and Optimization Problems – 2
1. 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
Answer: a
2. Mark two main features of Genetic Algorithm
a) Fitness function
b) Cross-over techniques
c) Individuals among the population
d) Random mutation
Answer: a, b
3. Which search agent operates by interleaving computation and action?
a) Offline search
b) Online search
c) Breadth-first search
d) Depth-first search
Answer: b
4. What is called as exploration problem?
a) State and actions are unknown to the agent
b) State and actions are known to the agent
c) Only actions are known to agent
d) Both b & c
Answer: a
5. In which state spaces does the online-dfs-agent will
work?
a) Irreversible state spaces
b) Reversible state spaces
c) searchable state spaces
d) All of the mentioned
Answer: b
6. Which search algorithm will use limited amount of
memory?
a) RBFS
b) SMA*
c) Hill-climbing search algorithm
d) Both a & b
Answer: d
7. How the new states are generated in genetic
algorithm?
a) Composition
b) Mutation
c) Cross-over
d) Both b & c
Answer: d
8. 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
Answer: a
9. Which of the following algorithm is online search
algorithm?
a) Breadth-first search algorithm
b) Depth-first search algorithm
c) Hill-climbing search algorithm
d) None of the mentioned
Answer: c
10. Searching using query on Internet is, use of
___________ type of agent
a) Offline agent
b) Online agent
c) Both a & b
d) Goal Based
Answer: b, d
Constraints Satisfaction Problems – 1
1. _________________ are mathematical problems
defined as a set of objects whose state must satisfy a
number of constraints or limitations.
a) Constraints Satisfaction Problems
b) Uninformed Search Problems
c) Local Search Problems
d) Only a) and b)
Answer: a
2. Which of the Following problems can be modeled as
CSP?
a) 8-Puzzle problem
b) 8-Queen problem
c) Map coloring problem
d) Sudoku
Answer: a, b, c, d
3. What among the following constitutes to the
incremental formulation of CSP?
a) Path cost
b) Goal cost
c) Successor function
d) Objective function
e) Initial state
Answer: a, b, c, e
4. 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
Answer: b
5. To overcome the need to backtrack in constraint
satisfaction problem can be eliminated by
a) Forward Searching
b) Constraint Propagation
c) Backtrack after a forward search
d) Omitting the constraints and focusing only on goals
Answer: a, b
7. Consider a problem of preparing a schedule for a class
of student. This problem is a type of
a) Search Problem
b) Backtrack Problem
c) CSP
d) Planning Problem
Answer: c
8. 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) DFS/BFS Search Algorithms
Answer: a, b, c, d
9. Solving a constraint satisfaction problem on a finite
domain is an/a ___________ problem with respect to
the domain size.
a) P complete
b) NP complete
c) NP hard
d) Domain dependent
Answer: b
10. ____________ is/are useful when the original
formulation of a problem is altered in some way,
typically because the set of constraints to consider
evolves because of the environment.
a) Static CSPs
b) Dynamic CSPs
c) Flexible CSPs
d) None of the above
Answer: b
Constraints Satisfaction Problems – 2
1. Flexible CSPs relax on,
a) Constraints
b) Current State
c) Initial State
d) Goal State
Answer: a
2. Language/Languages used for programming Constraint
Programming includes
a) Prolog
b) C++
c) C
d) Fortrun
Answer: a, b
3. Which search agent operates by interleaving
computation and action?
a) Offline search
b) Online search
c) Breadth-first search
d) Depth-first search
Answer: b
4. Backtracking is based on,
a) Last in first out
b) First in first out
c) Recursion
d) Both a & c
Answer: d
5. Constraint Propagation technique actually modifies
the CSP problem.
a) True
b) False
Answer: a
6. Which search algorithm will use limited amount of
memory?
a) RBFS
b) SMA*
c) Hill-climbing search algorithm
d) Both a & b
Answer: d
7. How many the new states are generated in
backtracking algorithm?
a) 1
b) 2
c) 3
d) 4
Answer: 1
8. When do we call the states are safely explored?
a) A goal state is unreachable from any state
b) A goal state is denied access
c) A goal state is reachable from every state
d) None of the mentioned
Answer: c
9. Which of the following algorithm is generally used CSP
search algorithm?
a) Breadth-first search algorithm
b) Depth-first search algorithm
c) Hill-climbing search algorithm
d) None of the mentioned
Answer: b
10. What do we mean by simulated annealing in artificial
intelligence?
a) Returns an optimal solution when there is a proper
cooling schedule
b) Returns an optimal solution when there is no proper
cooling schedule
c) It will not return an optimal solution when there is a
proper cooling schedule
d) None of the mentioned
Answer: a