WorksheetsAI Decision Making and Search Strategies
Total questions: 50
Worksheet time: 25mins
AI decision-making mainly aims to
Store data
Maximize rational outcomes
Reduce hardware cost
Replace humans
Which principle ensures an AI agent chooses the best possible action?
Learning
Autonomy
Rationality
Reactivity
An AI agent is defined as a system that
Stores knowledge only
Acts randomly
Perceives environment and acts upon it
Works without input
Which agent type acts only based on the current percept?
Goal-based agent
Learning agent
Utility-based agent
Simple reflex agent
Which AI agent maintains an internal model of the environment?
Simple reflex agent
Model-based agent
Utility-based agent
Learning agent
Goal-based agents select actions based on
Utility values
Random choice
Predefined rules
Achieving goals
Utility-based agents differ from goal-based agents because they
Do not learn
Ignore goals
Measure satisfaction levels
Work without sensors
Which characteristic allows an agent to operate without human intervention?
Reactivity
Autonomy
Learning
Rationality
Which agent improves its performance over time?
Reflex agent
Model-based agent
Learning agent
Goal-based agent
Developing a goal-based agent requires
No environment model
Fixed responses
Trial and error only
Search and planning techniques
Virtual assistants like Siri are examples of
Human agents
Autonomous AI agents
Manual systems
Rule-free systems
Recommendation systems mainly use AI agents to
Increase storage
Generate random content
Suggest relevant items
Replace databases
Autonomous vehicles depend heavily on
Static rules
Human drivers
AI agents and sensors
Manual control
AI agents in healthcare are commonly used for
File storage
Diagnosis and prediction
Hardware maintenance
Network setup
Who proposed the Turing Test?
John McCarthy
Marvin Minsky
Alan Turing
Herbert Simon
The term “Artificial Intelligence” was coined in
1945
1950
1956
1965
Deep Blue defeated the world chess champion in
1985
1997
2005
2012
A major breakthrough in deep learning occurred in
1990
2000
2005
2012
Explainable AI focuses on
Faster execution
Reduced cost
Transparency of decisions
Hardware optimization
Artificial General Intelligence refers to
Narrow task-specific AI
Rule-based systems
Human-level intelligence
Database systems
Ethical AI mainly addresses
Speed improvement
Data storage
Fairness and responsibility
Hardware usage
The first step in data processing is
Prediction
Classification
Data collection
Visualization
Pattern recognition is mainly used to
Delete data
Identify trends
Store information
Encrypt files
Which technique helps AI agents learn from data?
Data compression
Machine learning
Manual coding
File handling
AI agents use data processing mainly for
Entertainment only
Random decisions
Decision support
Hardware control
TensorFlow and PyTorch are
Databases
Programming languages
AI frameworks
Operating systems
Data cleaning helps to
Increase noise
Remove irrelevant data
Duplicate records
Corrupt datasets
Classification in AI refers to
Sorting data into categories
Deleting files
Encrypting data
Random selection
Prediction tasks in AI are used to
Guess randomly
Identify past data
Forecast future outcomes
Store history
AI agents processing customer data are commonly used in
Weather forecasting only
Education only
Marketing and sales
Hardware repair
A state space in AI represents
Only the initial state
All possible solutions
All possible states of a problem
Only goal states
Which of the following defines the goal of state space search?
To generate all states
To minimize memory usage
To find a path from initial to goal state
To avoid loops
Uniform Cost Search expands the node with
Lowest depth
Highest heuristic value
Lowest path cost
Highest path cost
Which data structure is used in Uniform Cost Search?
Stack
Queue
Priority Queue
Deque
Breadth-First Search (BFS) uses
Stack
Priority Queue
Queue
Heuristic function
Depth-First Search (DFS) is NOT suitable when
Memory is limited
Solution is very deep
Infinite state space exists
Search space is small
BFS is complete because
It explores deeply
It avoids cycles
It explores all nodes level by level
It uses heuristics
Which search strategy uses a depth limit to avoid infinite paths?
BFS
DFS
Uniform Cost Search
Depth-Limited Search
Depth-Limited Search fails when
Limit is zero
Goal is beyond depth limit
Memory is large
Heuristic is accurate
Bidirectional search works by
Searching randomly
Searching only from goal
Searching from start and goal simultaneously
Searching using heuristics
Bidirectional search is efficient because
It uses heuristics
It reduces search depth
It avoids goal testing
It uses DFS
Best-First Search selects nodes based on
Path cost
Depth
Heuristic value
Alphabetical order
A heuristic function estimates
Cost from start to node
Cost from node to goal
Total cost of path
Number of nodes
The evaluation function of A algorithm is
f(n) = h(n)
f(n) = g(n)
f(n) = g(n) + h(n)
f(n) = g(n) − h(n)
A algorithm is optimal when
h(n) = 0
h(n) is admissible
g(n) is maximum
Search space is infinite
Which of the following is an informed search strategy?
BFS
DFS
Uniform Cost Search
A* Search
Which search strategy guarantees optimal solution with unit step cost?
DFS
BFS
Best-First Search
Depth-Limited Search
In uninformed search, the search strategy
Uses domain knowledge
Uses heuristics
Has no additional problem knowledge
Always finds optimal solution
Which of the following is a real-world application of A?
Spell checking
Web crawling
GPS navigation
Text summarization
Compared to uninformed search, informed search is generally
Slower
Less efficient
More memory efficient
Faster and goal-directed
