Q#1: A simple decision in AI is one where:
(A) There is a single decision to make with known outcomes
(B) Multiple sequential decisions are required
(C) BFS nodes only
(D) DFS only
Answer: (A) There is a single decision to make with known outcomes
Q#2: Decision theory combines:
(A) Probabilities and utilities
(B) Only probabilities
(C) Only utilities
(D) BFS only
Answer: (A) Probabilities and utilities
Q#3: A utility function represents:
(A) Preferences over possible outcomes
(B) Probabilities of events
(C) BFS only
(D) DFS only
Answer: (A) Preferences over possible outcomes
Q#4: Expected utility is:
(A) Sum of utilities weighted by probabilities of outcomes
(B) Maximum probability of any outcome
(C) BFS only
(D) DFS only
Answer: (A) Sum of utilities weighted by probabilities of outcomes
Q#5: A rational agent chooses:
(A) Action that maximizes expected utility
(B) Action at random
(C) BFS only
(D) DFS only
Answer: (A) Action that maximizes expected utility
Q#6: Decision under certainty means:
(A) The outcome of each action is known
(B) Probabilities are uncertain
(C) BFS only
(D) DFS only
Answer: (A) The outcome of each action is known
Q#7: Decision under uncertainty means:
(A) Outcomes are probabilistic
(B) Outcomes are known with certainty
(C) BFS only
(D) DFS only
Answer: (A) Outcomes are probabilistic
Q#8: A payoff table lists:
(A) Outcomes and corresponding utilities for each action
(B) Probabilities only
(C) BFS only
(D) DFS only
Answer: (A) Outcomes and corresponding utilities for each action
Q#9: Probabilistic decision making uses:
(A) Expected utility to select the best action
(B) Random selection only
(C) BFS only
(D) DFS only
Answer: (A) Expected utility to select the best action
Q#10: In a decision network:
(A) Chance nodes represent uncertain events
(B) Only deterministic actions exist
(C) BFS only
(D) DFS only
Answer: (A) Chance nodes represent uncertain events
Q#11: Decision nodes represent:
(A) Choices available to the agent
(B) Probabilities of events
(C) BFS only
(D) DFS only
Answer: (A) Choices available to the agent
Q#12: Utility nodes represent:
(A) Agent preferences for outcomes
(B) Chance events
(C) BFS only
(D) DFS only
Answer: (A) Agent preferences for outcomes
Q#13: Simple decisions assume:
(A) One-step decision with no sequential dependencies
(B) Multiple sequential decisions
(C) BFS only
(D) DFS only
Answer: (A) One-step decision with no sequential dependencies
Q#14: A risk-averse agent prefers:
(A) Lower variance in outcomes
(B) Highest possible utility regardless of risk
(C) BFS only
(D) DFS only
Answer: (A) Lower variance in outcomes
Q#15: A risk-neutral agent prefers:
(A) Maximum expected utility without considering variance
(B) Minimum risk
(C) BFS only
(D) DFS only
Answer: (A) Maximum expected utility without considering variance
Q#16: A risk-seeking agent prefers:
(A) Higher variance in outcomes
(B) Low variance only
(C) BFS only
(D) DFS only
Answer: (A) Higher variance in outcomes
Q#17: Expected utility is computed by:
(A) Multiplying outcome probabilities by their utilities and summing
(B) Taking maximum probability only
(C) BFS only
(D) DFS only
Answer: (A) Multiplying outcome probabilities by their utilities and summing
Q#18: Probabilities in decision making can be:
(A) Subjective or objective
(B) Only objective
(C) Only subjective
(D) BFS only
Answer: (A) Subjective or objective
Q#19: A lottery in decision theory is:
(A) A set of outcomes with associated probabilities
(B) A random event only
(C) BFS only
(D) DFS only
Answer: (A) A set of outcomes with associated probabilities
Q#20: Determining the best decision involves:
(A) Comparing expected utilities of available actions
(B) Choosing at random
(C) BFS only
(D) DFS only
Answer: (A) Comparing expected utilities of available actions
Q#21: Conditional probabilities are used when:
(A) Outcomes depend on uncertain events
(B) Outcomes are certain
(C) BFS only
(D) DFS only
Answer: (A) Outcomes depend on uncertain events
Q#22: Utility functions can be:
(A) Linear, exponential, or customized
(B) Only linear
(C) Only exponential
(D) BFS only
Answer: (A) Linear, exponential, or customized
Q#23: Simple decision making does not consider:
(A) Sequential dependencies
(B) Probabilities
(C) Utilities
(D) BFS only
Answer: (A) Sequential dependencies
Q#24: Decision analysis often uses:
(A) Decision trees
(B) BFS only
(C) DFS only
(D) Random assignments
Answer: (A) Decision trees
Q#25: In a decision tree:
(A) Branches represent possible outcomes of actions
(B) Nodes only represent actions
(C) BFS only
(D) DFS only
Answer: (A) Branches represent possible outcomes of actions
Q#26: Leaf nodes in decision trees represent:
(A) Outcome utilities
(B) Probabilities only
(C) BFS only
(D) DFS only
Answer: (A) Outcome utilities
Q#27: Expected utility helps:
(A) Rank actions based on rational choice
(B) BFS only
(C) DFS only
(D) Random assignments
Answer: (A) Rank actions based on rational choice
Q#28: Sensitivity analysis in decision making evaluates:
(A) Effect of changing probabilities or utilities on decisions
(B) BFS only
(C) DFS only
(D) Random assignments
Answer: (A) Effect of changing probabilities or utilities on decisions
Q#29: Simple decisions are often:
(A) One-shot, single-step choices
(B) Multi-step sequential decisions
(C) BFS only
(D) DFS only
Answer: (A) One-shot, single-step choices
Q#30: Decision networks are graphical models for:
(A) Representing and solving decision problems
(B) BFS only
(C) DFS only
(D) Random assignments
Answer: (A) Representing and solving decision problems
Q#31: Probabilistic reasoning is essential for:
(A) Making decisions under uncertainty
(B) Deterministic environments only
(C) BFS only
(D) DFS only
Answer: (A) Making decisions under uncertainty
Q#32: Maximum expected utility criterion ensures:
(A) Rational choice according to preferences
(B) Random choice
(C) BFS only
(D) DFS only
Answer: (A) Rational choice according to preferences
Q#33: Utility theory allows:
(A) Quantitative comparison of outcomes
(B) BFS only
(C) DFS only
(D) Random assignments
Answer: (A) Quantitative comparison of outcomes
Q#34: Probabilities can be updated using:
(A) Bayes’ theorem
(B) BFS only
(C) DFS only
(D) Random assignments
Answer: (A) Bayes’ theorem
Q#35: Simple decisions assume:
(A) All actions and outcomes are considered in one step
(B) Multi-step planning
(C) BFS only
(D) DFS only
Answer: (A) All actions and outcomes are considered in one step
Q#36: In decision trees, probabilities on branches represent:
(A) Likelihood of each outcome
(B) Utility only
(C) BFS only
(D) DFS only
Answer: (A) Likelihood of each outcome
Q#37: A rational agent will:
(A) Choose the action with highest expected utility
(B) BFS only
(C) DFS only
(D) Random action
Answer: (A) Choose the action with highest expected utility
Q#38: Decision-making under risk uses:
(A) Known probabilities for outcomes
(B) Unknown probabilities
(C) BFS only
(D) DFS only
Answer: (A) Known probabilities for outcomes
Q#39: Decision-making under uncertainty uses:
(A) Probabilistic models
(B) Deterministic models only
(C) BFS only
(D) DFS only
Answer: (A) Probabilistic models
Q#40: Sensitivity analysis helps to:
(A) Test robustness of decisions to changes in probabilities/utilities
(B) BFS only
(C) DFS only
(D) Random assignments
Answer: (A) Test robustness of decisions to changes in probabilities/utilities
Q#41: Decision making requires:
(A) Identifying alternatives, outcomes, probabilities, and utilities
(B) BFS only
(C) DFS only
(D) Random assignment
Answer: (A) Identifying alternatives, outcomes, probabilities, and utilities
Q#42: Probabilistic reasoning allows:
(A) Rational choice when outcomes are uncertain
(B) Deterministic choice only
(C) BFS only
(D) DFS only
Answer: (A) Rational choice when outcomes are uncertain
Q#43: Expected utility maximization leads to:
(A) Optimal one-step decision
(B) Suboptimal choice always
(C) BFS only
(D) DFS only
Answer: (A) Optimal one-step decision
Q#44: Simple decision-making does not consider:
(A) Sequential dependencies or future consequences
(B) Current outcomes
(C) Probabilities
(D) Utilities
Answer: (A) Sequential dependencies or future consequences
Q#45: Decision networks can solve:
(A) Single-step or simple decision problems efficiently
(B) Multi-step planning only
(C) BFS only
(D) DFS only
Answer: (A) Single-step or simple decision problems efficiently
Q#46: Probabilistic reasoning in decision making:
(A) Combines likelihoods and preferences
(B) BFS only
(C) DFS only
(D) Random assignments
Answer: (A) Combines likelihoods and preferences
Q#47: Simple decision-making is foundational for:
(A) More complex sequential decision-making
(B) Only one-step choices
(C) BFS only
(D) DFS only
Answer: (A) More complex sequential decision-making
Q#48: Utility functions allow:
(A) Quantitative comparison of different outcomes
(B) BFS only
(C) DFS only
(D) Random assignments
Answer: (A) Quantitative comparison of different outcomes
Q#49: Probabilistic reasoning supports:
(A) Rational action selection under uncertainty
(B) Deterministic choice only
(C) BFS only
(D) DFS only
Answer: (A) Rational action selection under uncertainty
Q#50: The main goal of making simple decisions in AI is:
(A) Choose the best action based on expected utility
(B) BFS only
(C) DFS only
(D) Random assignments
Answer: (A) Choose the best action based on expected utility