NEW
Font size
WorksheetsAI U1 and U2
Total questions: 40
Worksheet time: 20mins
Who coined the term Artificial Intelligence?
Alan Turing
Marvin Minsky
John McCarthy
Andrew Ng
Which of the following is a rational agent?
One that acts like a human
One that guesses outcomes randomly
One that acts to achieve the best expected outcome
One that imitates a machine
Which type of search uses a heuristic function only?
Breadth First Search
Depth First Search
Greedy Best-First Search
Uniform Cost Search
What does the ‘Suck’ action do in the Erratic Vacuum World?
Always cleans the tile
Cleans tile but may behave unpredictably
Only moves the agent
Turns off the agent
Which game is a perfect information game?
Poker
Backgammon
Chess
Bridge
In resolution, two clauses are resolved if they have
Common literals
Complementary literals
Identical literals
Random variables
In a partially observable environment, agents rely on:
Belief states
Perfect sensors
Turing test
Logical rules
What is the main disadvantage of Hill Climbing?
Memory overhead
High branching factor
Stuck in local maxima
No heuristic use
Which environment characteristic describes “Rolling a dice”?
Deterministic
Stochastic
Discrete
Static
Which agent type maintains an internal state?
Simple Reflex Agent
Model-Based Reflex Agent
Utility-Based Agent
Goal-Based Agent
Simulated Annealing allows:
Only upward moves
Downhill moves with some probability
No random moves
Constant temperature
Which of these is not a step in Genetic Algorithm?
Selection
Fitness Function
Survival of the fittest
Crossover
Agent = Architecture + ___________ ?
Sensors
Actuators
Program
Logic
Which inference rule allows you to derive Q from (P ⇒ Q) and P
And Or Elimination
Modus Ponens
Monotonicity
Resolution
Which of these is an informed search strategy?
DFS
BFS
Iterative Deepening
A*
Which of the following has a single path and explores only neighbors?
BFS
DFS
Hill Climbing
A*
What is the evaluation function in A?*
f(n) = h(n)
f(n) = g(n)
f(n) = g(n) + h(n)
f(n) = h(n) – g(n)
Which problem is typically used to demonstrate partial observability?
8 Puzzle
Wumpus World
TSP
Vacuum World
AND-OR search trees are useful in:
Deterministic environments
Linear problems
Nondeterministic environments
BFS
What is the effect of the Horizon Effect in game playing?
Allows agents to see beyond the goal
Misses deep consequences of current moves
Improves evaluation accuracy
Increases memory efficiency
Which of the following is not an uninformed search method?
DFS
Uniform Cost
BFS
Beam Search
In the Game Tree, nodes represent:
Moves
Players
States
Solutions
The A search guarantees optimality if:*
h(n) is always zero
h(n) never overestimates
h(n) > g(n)
g(n) is random
Which condition causes Alpha-Beta pruning to be most effective?
Balanced trees
Random node ordering
Ideal node ordering
Worst Node Ordering
Which two logical connectives are used to form Conjunctive Normal Form (CNF)?
AND and NOT
OR and NOT
AND and OR
XOR and NOT
In the Wumpus world, a breeze indicates:
A pit is in the same cell
Wumpus is near
A pit is adjacent
Gold is nearby
Contingency plans are necessary in which case?
Fully observable environment
Static and known world
Nondeterministic environment
Reflex agents
Evaluation functions should ideally be:
Complex and feature-rich
Fast, stable, and mimic utility
Randomly generated
Avoid wins
Which of these is not a component of the Wumpus agent?
Sensors
Perception Logic
Actuators
Database
What does “quiescent position” mean in game search?
Rapidly changing state
Stable state with no big changes
Goal state
Winning state
Why does forward pruning risk error?
It skips random branches
It ignores opponents' moves
It may discard optimal moves
It uses no heuristic
What is the purpose of the knowledge base in a logical agent?
Storing percept history
Executing random actions
Storing rules and facts for inference
Collecting statistics
Which is true about Online Search Agents?
Plan everything before acting
Learn the environment during action
Act in offline worlds
Cannot handle dynamic states
Backward chaining works by:
Applying rules to facts
Checking all possible outcomes
Working from goal to facts
Forward logic
In the context of heuristic search, h(n) represents:
The cost from the start node to n
The cost from node n to the goal
Total path cost
Branching factor
Which type of game includes chance nodes along with MAX and MIN nodes?
Perfect information games
Deterministic games
Stochastic games
Multi-agent deterministic games
Which of the following is a component of the PEAS framework?
Plan
Environment
Algorithm
Execution
What type of agent simply reacts to the current percept without memory?
Utility-Based Agent
Model-Based Agent
Goal-Based Agent
Simple Reflex Agent
In the context of the Game Tree, what does the Minimax algorithm assume about the opponent?
The opponent plays randomly
The opponent tries to maximize your score
The opponent plays optimally to minimize your score
The opponent does not make a move
Which of the following search methods uses a predetermined depth limit?
Uniform Cost Search
Iterative Deepening DFS
Depth Limited Search
Breadth First Search
