Quiz Questions

Question 1

[Prob] Bayes’ Theorem is used in constructing ________

Answer 1

belief networks

Question 2

[Lecture12] According to the class discussion, _____ probability associated with proposition X is the degree of belief accorded to it in the absence of any other information

Answer 2

prior

Question 3

[Lecture12] According to the class discussion.Consider the wumpus world as shown below.

The Known facts are: { not Pit[1,1], not Pit[1,2], not Pit[2,1] }, and the presence of breeze (denoted as b) in cells: b = { b[1,2], b[2,1] }. The Query is for the probability of Pit in each frontier cell of { [1,3], [2,2], [3,1] }, and especially to compute what is the probability of Pit in the cell [1,3], that is, P(Pit[1,3]).
What is the normalization constant for this case to compute P(Pit13|known,b)?
Select the best answer as discussed in the class.

Answer 3

1/((0.2)3 + 3x(0.2)2x0.8 + 0.2x(0.8)2)

Question 4

Lecture12] According to the class discussion. Consider two random variables s and m. Which one of the following is NOT correct?

Answer 4

P(s|m) = P(s,m) / [P(m|s)P(m) + P(m|¬s)P(m)]

Question 5

[Prob] Uncertainty is a property of all environments that are ____________

Answer 5

partially observable or stochastic

Question 6

[Lecture12] According to the class discussion.There are two discrete random variables X and Y where X describes weather conditions, with the domain: X={sunny, rain, cloudy, snow}, and Y describes clothes to wear, with the domain: Y={t-shirt, long-sleeves, coat}. The distributions of X and Y are:
X = <0.331, 0.26, 0.159, 0.25>
Y = <0.5, 0.3, 0.2>
And the joint probabilities are:
P(t-shirt, sunny)=0.32 P(t-shirt, rain)=0.08 P(t-shirt, cloudy)=0.09
P(t-shirt, snow)=0.01 P(long-sleeves, sunny)=0.01 P(long-sleeves, rain)=0.15
P(long-sleeves, cloudy)=0.05 P(long-sleeves, snow)=0.09 P(coat, sunny)=0.001
P(coat, rain)=0.03 P(coat, cloudy)=0.019 P(coat, snow)=0.15

To guess the weather from the clothes people wear: P(X|Y), What is Normalization Constant α to compute P(sunny | t-shirt).

Answer 6

α (0.32+0.08+0.09+0.01) = 1

Question 7

[Lecture12] According to the class discussion.Consider the axioms of Probability (where a and b are random variables). Which one of the following is NOT correct?

Answer 7

P(a ∧ b) = P(a) * P(b)

Question 8

[Lecture12] Consider the following table as we discussed in the class.

toothache not toothache
————|——————|———————|
catch !catch | catch !catch
————|——-|———–|———-|———–|
cavity | 0.18 | 0.012 | 0.072 | 0.0008
————|——-|———–|———-|———–|
!cavity | 0.016 | 0.064 | 0.144 | 0.576
————|——-|———–|———-|———–|

Let X be P(cavity | toothache), where αbe the normalization constant and X = αP(cavity, toothache). Then α = __________.

Answer 8

1/P(cavity, toothache)

Question 9

[Prob] Probabilities are employed in ________ methods.

Answer 9

stochastic

Question 10

[Prob] Beliefs ____________.

Answer 10

are changeable

Question 11

[Lecture13] According to the class discussion. Consider the following probability tables for fever (concerning only three causes of cold, flu, malaria). These causes are independent of each other and are all causes of Fever.

What is the P(Fever |¬ Cold, ¬ Flu, Malaria) for the Entry (2)?

Probabilities of individual inhibitions
P( fever | cold, flu, malaria) = 0.6
P(-fever | -cold, flu, malaria) = 0.2
P(-fever| -cold, flu,malaria) = 0.1

From this information, the entire CPT can be built

Answer 11

0.9

Question 12

[Lecture13] According to the class discussion. Which one of the following is NOT correct?The Bayesian Network consists of or is: ________.

Answer 12

A graph which may have a cycle but with leaf node only.

Question 13

[Lecture13] According to the class discussion.Consider the following probability tables for fever (concerning only three causes of cold, flu, malaria). These causes are independent of each other and are all causes of Fever.
What is the P(Fever | ¬ Cold, ¬ Flu, ¬ Malaria) for the Entry (1)?

Answer 13

0.0

Question 14

[Lecture13] According to the class discussion.Consider the following factoring equation and tables provided.
What is the answer for entry (1) in Table f(ExAxJxM) (that is, the right-most table)?

Answer 14

(E1) x (F1) + (E2) x (F2)

Question 15

[AI-Ch10Plan] According to the authors. If we add function symbols to the language (e.g., blocks world), then _____.Which one of the following statements is NOT correct?

Answer 15

The Bounded problem remains undecidable even in the presence of function symbols.

Question 16

[AI-Ch10Plan] According to the authors. Consider PDDL. Actions are described by a set of action schemas that implicitly define the ACTIONS(s) and _____ functions needed to do a problem-solving search.

Answer 16

RESULT(s, a)

Question 17

[AI-Ch10Plan] According to the authors. The subgoal independence assumption can be ______ when subplans contain redundant actions—for instance, two actions that could be replaced by a single action in the merged plan.

Answer 17

pessimistic

Question 18

[AI-Ch10Plan] According to the authors. The ______ heuristic drops all preconditions from action becomes applicable in every state, and any single goal fluent can be achieved in one step (if there is an applicable action—if not, the problem is impossible).

Answer 18

ignore preconditions

Question 19

[AI-Ch10Plan] According to the authors. Consider PDDL. Which one of the following statements is NOT correct?

Answer 19

A fluent can be treated as a disjunction of potential actions, which can be manipulated with set operations.

(A in ACTIONS(S)) if and only if PRECONDITION(A) entails S.

The set of action schema provides the state of the system in planning.

Question 20

[AI-Ch10Plan] According to the authors. With a planning graph, one can estimate the cost of achieving any goal literal G from a state S as the level at which the goal literal G first appears in planning graph constructed from initial state S. We call this the ______ of G.

Answer 20

level cost

Question 21

[AI-Ch10Plan] According to the authors. Consider Planning Graph. To estimate the cost of a conjunction of goals, there are three simple approaches. The ____ heuristic, following the subgoal independence assumption, returns the sum of the level costs of the goals.

Answer 21

level-sum

Question 22

[AI-Ch10Plan] According to the authors. Consider Planning Graph. For some heuristic guidance for choosing among actions during the backward search, one approach that works well in practice is a greedy algorithm based on the level cost of the literals. For any set of goals, we proceed in the fallowing order: Pick first the literal with the (1) ____ level cost. To achieve that literal, prefer actions with easier preconditions. That is, choose an action such that the sum (or maximum) of the level costs of its preconditions is (2) ____.

Answer 22

highest, smallest

Question 23

[AI-Ch10Plan] According to the authors. The result of executing action A in state S is defined as a state S’ which is represented by the set of fluents formed by starting with S. Which one of the following statements is NOT correct?

Answer 23

As with all states, the open-world assumption is used. That is, any atoms that are not mentioned are false.

The fluents in the action schema should explicitly refer to time of each action.

Question 24

[AI-Ch10Plan] According to the authors. Consider Planning Graph. Planning is ______.

Answer 24

PSPACE-complete

Question 25

[AI-Ch10Plan] According to the authors. Consider Planning. First-order logic lets us get around this limitation by replacing the notion of linear time with a notion of branching situations, using a representation called _____.

Answer 25

Situation Calculus

Question 26

[AI-Ch10Plan] According to the authors. Consider Planning Graph. Which one of the following choices is NOT correct?

Answer 26

-Literals decrease monotonically. -No-goods could increase monotonically. -Planning graphs can work withapredicated planning with some variables. -Planning graph shows each Ai level which contains all the fluents that are applicable in Si. -The consistency of an action at one level assures the preconditions and effects at one level to the next.

Question 27

[AI-Ch10Plan] According to the authors. Consider Situation Calculus. The agent can deduce that an action A is unique and different from other actions. This is a(n) _____ axiom.

Answer 27

unique action

Question 28

[AI-Ch10Plan] According to the authors. Consider Situation Calculus. A function or relation that can vary from one situation to the next is a(n) _____.

Answer 28

fluent

Question 29

[AI-Ch10Plan] According to the authors. The reason for the state, "not Poor," is NOT allowed in PDDL because _____.

Answer 29

it is negated

Question 30

[AI-Ch10Plan] According to the authors. Consider PDDL. Any system for action description needs to solve the ____ problem—to say what changes and what stays the same as the result of the action.

Answer 30

frame

Question 31

AI-Ch10Plan] According to the authors. For Algorithms for Planning as State-Space Search. The description of a planning problem defines a search problem: we can search from the initial state through the space of states, looking for a goal. From the earliest days of planning research (around 1961) until around 1998 it was assumed that forward state-space search _____. Which one of the following statements is NOT correct?

Answer 31

can be very efficient as it tries to narrow the search space by focusing on the goal forward.

Question 32

[AI-Ch10Plan] According to the authors. The reason for the state, At(x,y), is NOT allowed in PDDL because _____.

Answer 32

it is not grounded

Question 33

[AI-Ch10Plan] According to the authors. One issue in planning is deciding which actions are candidates to regress over. In the forward direction we chose actions that were (1) _____ —those actions that could be the next step in the plan. In backward search we want actions that are (2) _____ —those actions that could be the step in a plan leading up to the current goal state.

Answer 33

applicable, relevant

Question 34

[AI-Ch10Plan] According to the authors. The following statements describe the _____ heuristic.Assume for a moment that all goals and preconditions contain only positive. We want to create a relaxed version of the original problem that will be easier to solve, and where the length of the solution will serve as a good heuristic. We can do that by removing all negative literals from effects from all actions. That makes it possible to make monotonic progress towards the goal—no action will ever undo progress made by another action.

Answer 34

ignore delete-lists

Question 35

[Prob] Stochastic methods are often used in ___________

Answer 35

planning under uncertainty

Question 36

[Lecture12] According to the class discussion.Consider a Medical diagnosis for Meningitis which is a disease caused by the inflammation of the protective membranes covering the brain and spinal cord known as the meninges. A doctor knows that meningitis causes a stiff neck 50% of the time: P(s|m)=0.5. The doctor also knows some unconditional facts: the prior probability that the patient has meningitis is 1/50000. That is, P(m)=1/50000. The prior probability that any patient has a stiff neck is 1/20. That is, P(s)=1/20. What is P(m | s)?

Answer 36

[ 0.5 x (1/50000) ] / (1/20)

Question 37

[Prob] Partial-information games are solved using ___________.

Answer 37

belief states

Question 38

[Prob] Given a sample space S, the probability of S is ________

Answer 38

1

Question 39

[Prob] Given a sample space S which is not empty, the probability of an empty set is ________.

Answer 39

0

Question 40

[Prob] Bayesian reasoning is ___________

Answer 40

diagnostic

Question 41

[Lecture12] Consider the following table as we discussed in the class. What is P(cavity | toothache)?

Answer 41

( (0.108 + 0.012) / (0.108 + 0.012 + 0.016 + 0.064) )