WorksheetsAI Concepts Quiz
Total questions: 25
Worksheet time: 13mins
What does an AI agent perceive to make decisions?
Actions
Environment
Sensors
Goals
A fully observable environment means the agent:
Has limited information
Can perceive the entire state of the environment at all times
Acts randomly
Has no knowledge of the environment
Which of the following agents maintains an internal state to handle partially observable environments?
Simple reflex agent
Model-based reflex agent
Goal-based agent
Utility-based agent
The concept of rationality in AI means the agent:
Chooses actions randomly
Chooses actions that maximize expected performance
Always acts optimally regardless of environment
Does not learn from experience
Which of the following is NOT an uninformed search algorithm?
Breadth-First Search
Depth-First Search
A* Search
Uniform Cost Search
In informed search strategies, the function used to estimate the cost from the current state to the goal is called:
Path cost
Heuristic function
Utility function
Performance measure
Which search algorithm expands the shallowest unexpanded node first?
Depth-First Search
Breadth-First Search
Uniform Cost Search
Greedy Best-First Search
What is the primary disadvantage of Depth-First Search (DFS)?
Requires a lot of memory
Can get stuck in infinite loops
Always finds the shortest path
Uses heuristics inefficiently
The goal of a problem-solving agent is to:
Explore the environment randomly
Find a sequence of actions leading to the goal state
Execute predefined actions without searching
Learn new goals automatically
Which of the following best describes a static environment?
Environment changes over time
Environment remains unchanged while agent is deciding
Environment is unpredictable
Agent cannot perceive environment
In AI, the term 'performance measure' refers to:
How fast the agent runs
Criteria to evaluate agent's success
The agent's programming language
Memory usage of the agent
Which agent type uses a utility function to choose among multiple goals?
Simple reflex agent
Model-based agent
Utility-based agent
Goal-based agent
Which search strategy uses both path cost and heuristic value to find optimal solutions?
Uniform Cost Search
A* Search
Greedy Best-First Search
Depth-First Search
What does it mean if an environment is deterministic?
Next state depends only on current state and action
Next state is random
Environment changes unpredictably
Agent cannot perceive the environment
Which of the following is NOT true for uninformed search algorithms?
They use no domain knowledge
They expand nodes blindly
They always find optimal solutions
Examples include BFS and DFS
The main advantage of informed search over uninformed search is:
Less memory usage
Ability to use heuristics to guide the search
Simplicity in implementation
Always guaranteed to find a solution
Which agent type is best suited for environments where the agent has incomplete knowledge?
Simple reflex agent
Model-based agent
Random agent
Goal-based agent
What does the 'state transition model' describe?
How the agent moves physically
How actions change the environment state
Agent's internal memory
Performance evaluation criteria
Which of these search algorithms is complete (always finds a solution if one exists)?
Depth-First Search
Breadth-First Search
Greedy Best-First Search
Hill Climbing
The search tree of a problem-solving agent represents:
Possible sequences of actions
All known environments
Agent's programming code
Sensors and actuators
T/F: A simple reflex agent bases its actions solely on the current percept.
True
False
T/F: The A* search algorithm combines path cost and heuristic to optimize search.
True
False
T/F: In a stochastic environment, the outcome of actions is unpredictable.
True
False
T/F: Breadth-First Search uses a stack data structure.
True
False
T/F: Rational agents always perform the optimal action.
True
False
