WorksheetsAdversarial Search and CSP Quiz
Total questions: 31
Worksheet time: 16mins
What is the main objective of adversarial search in game theory?
To minimize the opponent's score
To maximize a player's score while minimizing the opponent's advantage
To predict future game states
To increase randomness in decision-making
In the Minimax algorithm, the "min" player tries to:
Maximize the opponent's score
Minimize their own score
Minimize the opponent's score
Maximize their own score
Which type of games is the Minimax algorithm most commonly used for?
Single-player games
Deterministic and two-player games
Stochastic games
Multi-agent decision-making games
What is the primary assumption in the Minimax algorithm?
Players make random moves
Opponent always plays optimally
Game has multiple optimal solutions
Players cooperate for mutual benefit
The complexity of the Minimax algorithm is:
O(log n)
O(n)
O(b^d)
O(n^2)
Alpha-Beta pruning improves Minimax by:
Reducing the number of nodes evaluated
Increasing the depth of search
Randomly selecting nodes
Ignoring terminal states
In Minimax, the depth of the search tree is:
Determined by the branching factor
Always infinite
Unimportant for evaluation
Never a factor
What is the best-case time complexity of Alpha-Beta pruning?
O(b^d)
O(b^(d/2))
O(d^b)
O(log b)
Alpha and Beta values in Alpha-Beta pruning represent:
The minimum and maximum score values found so far
Randomly assigned thresholds
Values determined at the end of the game
The probability of winning
Which of the following is an example of a CSP?
Chess
Sudoku
Stock market prediction
Image recognition
In CSPs, variables must satisfy:
At least one constraint
All constraints
A random set of constraints
A predefined number of constraints
Backtracking search in CSPs is used for:
Randomized search
Heuristic evaluation
Systematic constraint checking
Parallel computation
Crypt arithmetic puzzles are solved using:
Constraint satisfaction techniques
Probability models
Adversarial search
Reinforcement learning
What is the main challenge in Crypt arithmetic puzzles?
Assigning values to letters while satisfying constraints
Maximizing the sum of numbers
Minimizing the total assigned value
Randomly selecting digits
Room colouring problems are an example of:
Adversarial search
Constraint satisfaction problems
Heuristic learning
Neural networks
The primary goal in the room colouring problem is to:
Minimize the number of colors used
Maximize the number of colors used
Randomly assign colors
Predict future color assignments
An intelligent agent is one that:
Always succeeds in solving a problem
Acts rationally based on observations
Performs random actions
Ignores environmental changes
A rational agent aims to:
Maximize its performance measure
Randomly select actions
Minimize environmental interference
Learn from human intervention
Performance measures of an intelligent agent should be:
Subjective
Measurable and objective
Irrelevant
Undefined
Rationality of an agent depends on:
The percept sequence, knowledge, and performance measure
Random guessing
How much data it has
Ignoring external feedback
Which of the following is NOT a type of intelligent agent?
Reflex agent
Model-based agent
Genetic agent
Goal-based agent
A simple reflex agent:
Acts only on current percepts
Maintains an internal model
Uses past history
Learns from mistakes
A goal-based agent selects actions by:
Comparing goal states
Performing random actions
Minimizing computation
Following predefined rules
The task environment of an agent includes:
Performance measure, environment, actuators, and sensors
Only performance measures
Only external world data
Random event triggers
A deterministic environment means:
The outcome of actions is predictable
The environment is always uncertain
The agent has complete knowledge
The agent must learn through experience
What is the primary function of a model-based agent?
To perform random actions
To maintain an internal representation of the world
To act based solely on current percepts
To learn from past experiences only
In constraint satisfaction problems, what is a common method for finding solutions?
Depth-first search
Randomized algorithms
Greedy algorithms
Backtracking search
What does a goal-based agent primarily rely on to make decisions?
Current environmental conditions
Random chance
Predefined rules and heuristics
Evaluating potential future states
What is the main purpose of using heuristics in search algorithms?
To guarantee optimal solutions
To reduce search time and improve efficiency
To eliminate the need for evaluation functions
To increase randomness in decision-making
Which of the following best describes a constraint in a CSP?
A method for evaluating performance
A random selection of values
A rule that restricts the values that variables can take
A strategy for optimizing search
REGISTER NUMBER
(a)
