AI Final Exam Quiz Review CSC 480

Convert to Conjunctive Normal Form: (P -> (Q <-> R)) Question options: -(-P V -Q V -R) ^ (P V -Q V -R) -(-P V Q V R) ^ (-P V -Q V -R) -(-P V -Q V R) ^ (-P V Q V -R) -(P V Q V R) ^ (-P V -Q V -R) -none of the above

(-P V -Q V R) ^ (-P V Q V -R)

Which of the following would be a good constraint for the crossword problem? (Which apply?) Image: https://tinyurl.com/y5pcosul Question options: -1 across =/= 2 down -Alldiff(1,2,3,4) -length(4 across) = 4 -firstLetter(3 across) = thirdLetter(1 down)

1 across =/= 2 down & firstLetter(3 across) = thirdLetter(1 down)

Image: https://tinyurl.com/y6ozqdtt 1.Use Expect Minimax to calculate the value for node A: __ 2.Use Expect Minimax to calculate the value for node B: __

1. 1 2. -2

Image: https://tinyurl.com/yy5cfhdz 1. Using the min-max algorithm, what should the value for node E be? 2. What should the value for node F be? 3. What should the value for node G be? 4. What should the value for node H be? 5. What should the value for node I be? 6. What should the value for node J be? 7. What should the value for node B be? 8. What should the value for node C be? 9. What should the value for node D be? 10. What should the value for node A be?

1. 3 2. 9 3. 0 4. 7 5. 2 6. 6 7. 3 8. 0 9. 2 10. 3

Suppose that Bob can decide to go to work by one of three modes of transportation, car, bus, or commuter train. Because of high traffic, if he decides to go by car, there is a 50% chance he will be late. If he goes by bus, which has special reserved lanes but is sometimes overcrowded, the probability of being late is only 20%. The commuter train is almost never late, with a probability of only 1%, but is more expensive than the bus. Suppose that Bob is late one day, and his boss wishes to estimate the probability that he drove to work that day by car. Since he does not know which mode of transportation Bob usually uses, he gives a prior probability of 1/3 to each of the three possibilities. What is the boss' estimate of the probability that Bob drove to work? Question options: -33.33% -50% -68.23% -70.42%

70.42%

Suppose that a coworker of Bob's knows that he almost always takes the commuter train to work, never takes the bus, but sometimes, 10% of the time, takes the car. What is the coworkers probability that Bob drove to work that day, given that he was late? Question options: -33.33% -50.00% -69.56% -84.75%

84.75%

A says, "B is a knight" and B says, "The two of us are opposite types." Figure out whether each person is a knight or a knave from his or her statements. (Which apply). Question options: -A is a knight. -A is a knave. -It is not possible to know whether A is knight or a knave. -B is a knight. -B is a knave. -It is not possible to know whether B is knight or a knave.

A is a Knave & B is a Knave

A says, "We are both knaves" and B says nothing. Figure out whether each person is a knight or a knave from his or her statements. (Mark all that apply). Question options: -A is a knight. -A is a knave. -It is not possible to know whether A is knight or a knave. -B is a knight. -B is a knave. -It is not possible to know whether B is knight or a knave.

A is a knave & B is a knight

Recall the Island of Knight's and Knaves. You know that knights always tell the truth and knaves always lie. On the final exam, you are guaranteed to have a similar question. Practice writing out the statements in propositional logic and **derive** the solution. A says, "I am a knave or B is a knight" and B says nothing. Figure out whether each person is a knight or a knave from his or her statements. (Mark all that apply). Question options: -A is a knight. -A is a knave. -It is not possible to know whether A is knight or a knave. -B is a knight. -B is a knave. -It is not possible to know whether B is knight or a knave.

A is a knight & B is a knight

A constraint satisfaction problem consists of these components: (Which apply?) Question options: -A search algorithm -A set of constraints -A set of path costs -A set of variables -A set of domains for each variable

A set of constraints, A set of variables, & A set of domains for each variable

Now let us add a rule: a spy can lie or tell the truth. While traveling along a road with a knight you meet three strangers. The knight tells you, "I know these travelers. One is a spy. One is a knight. The other is a knave." A says that C is a knave. B says that A is a knight. C says, "I am the spy." Which one is the spy, which one is the knight, and which one is the knave? A. __ B.__ C.__ 1. Knight 2. Spy 3. Knave

A. Knight B. Spy C. Knave

Image: https://tinyurl.com/y3qh5t9o For iterative-deepening search, the order of nodes expanded would be...

AABCABDECFG

Question options: Use the following tree to indicate the order that nodes are expanded, for different types of search. Assume that A is the start node and G (double box) is the only goal node. Here, path costs are shown to the right of each path, g = cost of path so far, h = estimate of remaining cost to goal, f = estimate of total path cost. Image: https://tinyurl.com/y3qh5t9o For breadth-first search, the order of nodes expanded would be "ABCDEFG". For depth-first search, the order of nodes expanded would be...

ABDECFG

Image: https://tinyurl.com/y3qh5t9o For best-first search, the order of nodes expanded would be...

ABEDCG

Image: https://tinyurl.com/y3qh5t9o For uniform-cost search, the order of nodes expanded would be...

ACFG

Image: https://tinyurl.com/y3qh5t9o For A* search, the order of nodes expanded would be...

ACG

In order to pass the Turing test, you must design a machine that... - Thinks like a human? - Acts like a human? - Thinks rationally? - Acts rationally?

Acts like a human

An intelligent agent can search through the states of a CSP space more efficiently by answering the question(s)... (Which apply?) Question options: -Which variable should be assigned next? -In what order should its values be tried? -Can we detect inevitable failure early? -Can we take advantage of problem structure?

All of the above

Which of the following problems can be modeled as CSP? (Which apply?) Question options: -A New York Times Crossword -8-Queens problem -Map coloring problem -Sudoku

All of the above

The term ___________ is used for a depth-first search that chooses values for one variable at a time and returns when a variable has no legal values left to assign. -Forward search -Backtracking -Local search -Arc limited search

Backtracking

Imagine an agent designed to sell hot dogs at Wrigley Field. Its current goal state is to give(hotdog, Joe). Which planning technique would be most appropriate? Question options: -Forward Planning. The stadium holds thousands of individuals; we do not want the agent to evaluate give(hotdog, x) for every x. -Forward Planning. There are only a small number of actions our agent might perform relative to the number of people in the stadium. -Backward Planning. The stadium holds thousands of individuals; we do not want the agent to evaluate give(hotdog, x) for every x. -Backward Planning. There are only a small number of actions our agent might perform relative to the number of people in the stadium.

Backward Planning. The stadium holds thousands of individuals; we do not want the agent to evaluate give(hotdog, x) for every x.

Search strategies differ in the order of node expansion. The strategy from A*... Question options: -Operates on first in, first out -Operates on first in, last out -Expands the node with the lowest g(n) = distance from the start to n -Expands the node with the lowest h(n) = the estimate from n to the goal -Expands the node with the lowest f(n) = g(n) + h(n)

Expands the node with the lowest f(n) = g(n) + h(n)

Search strategies differ in the order of node expansion. The strategy from uniform-cost... Question options: -Operates on first in, first out -Operates on first in, last out -Expands the node with the lowest g(n) = distance from the start to n -Expands the node with the lowest h(n) = the estimate from n to the goal -Expands the node with the lowest f(n) = g(n) + h(n)

Expands the node with the lowest g(n) = distance from the start to n

Search strategies differ in the order of node expansion. The strategy from best-first... -Operates on first in, first out -Operates on first in, last out -Expands the node with the lowest g(n) = distance from the start to n -Expands the node with the lowest h(n) = the estimate from n to the goal -Expands the node with the lowest f(n) = g(n) + h(n)

Expands the node with the lowest h(n) = the estimate from n to the goal

Image: https://tinyurl.com/yy5cfhdz True or False: Assume that min-max explores nodes from left to right. For example it would explore E and the nodes below it before F. Using alpha-beta pruning, the search algorithm could have ignored node F and below.

False

Image: https://tinyurl.com/yy5cfhdz True or False: Using alpha-beta pruning, the search algorithm could have ignored node G and below.

False

Image: https://tinyurl.com/yy5cfhdz Using alpha-beta pruning, the search algorithm could have ignored node I and below.

False

True or False: Assume that a rook can move on a chessboard any number of squares in a straight line, vertically or horizontally, but cannot jump over other pieces; then Manhattan distance is an admissible heuristic for the problem of moving the rook from square A to square B in the smallest number of moves.

False

True or False: Depth-first search always expands at least as many nodes as A* search with an admissible heuristic.

False

True or False: Given the following knowledge base KB:... P P V Q ...the query Q is entailed by KB?

False

True or False: Goal-based agents choose actions that maximize its performance measure.

False

True or False: Learning-based agents are not compatible with other agent designs.

False

True or False: Model-based reflex agents have no memory.

False

True or False: Non-monotonic logics provide the means of reasoning with uncertainty.

False

True or False: One drawback of neural networks is that they only work on linearly separable spaces.

False

True or False: Popular search algorithms such as BFS, DFS and A* will usually solve constraint satisfaction problems efficiently.

False

True or False: Simple reflex agents maintain models of the observable world.

False

True or False: Simple reflex agents often incorporate search strategies.

False

True or False: Since the conditional probability tables of Bayesian Networks are often much smaller than the joint probability space, it is sometimes impossible to reproduce this space.

False

True or False: The heuristic from the tree above is admissible. Image: https://tinyurl.com/y3qh5t9o

False

True or False: The minimum remaining values heuristic will immediately detect failure in a branch because it chooses the variable with the greatest number of legal moves.

False

True or False: This environment is episodic (not sequential).

False

True or False: When mapping a real-world problem to a state space, the state representations should maintain as much detail as possible.

False

True or False: ∀x ∃y P(x, y) <-> ∃y ∀x P(x, y)

False

True or False: ∃x P(x) <-> ~∀x P(x)

False

True or False: Eliza passed the Turing test in the early sixties.

False

True or False: Given the richness of human emotion it is unlikely that an AI will ever pass the Turing test

False

Consider the statement, "If n is divisible by 30 then n is divisible by 2 and by 3 and by 5." Which of the following statements is equivalent to this statement? Question options: -If n is not divisible by 30 then n is divisible by 2 or divisible by 3 or divisible by 5. -If n is not divisible by 30 then n is not divisible by 2 or not divisible by 3 or not divisible by 5. -If n is divisible by 2 and divisible by 3 and divisible by 5 then n is divisible by 30. -If n is not divisible by 2 or not divisible by 3 or not divisible by 5 then n is not divisible by 30. -If n is divisible by 2 or divisible by 3 or divisible by 5 then n is divisible by 30.

If n is not divisible by 2 or not divisible by 3 or not divisible by 5 then n is not divisible by 30.

The STRIPS language requires... (Which apply?) Question options: -Initial State -Actions -Heuristics -Goal State

Initial State, Actions, & Goal State

A Goal state... (Which apply?) Question options: -Is represented as a conjunction of propositions. -Contains the necessary variables. -Is achieved when all sub goals are achieved. -May contain 'or's.

Is represented as a conjunction of propositions and Is achieved when all sub goals are achieved

Both A and B say, "I am a knight." Figure out whether each person is a knight or a knave from his or her statements. (Mark all that apply). Question options: -A is a knight. -A is a knave. -It is not possible to know whether A is knight or a knave. -B is a knight. -B is a knave. -It is not possible to know whether B is knight or a knave.

It is not possible to know whether A is knight or knave & It is not possible to know whether B is knight or knave

What are the Sensors? (Which apply?) -Doctors -Hospital -Keyboard -Administrator

Keyboard

Let v(x) mean x is a vegetarian, m(y) for meat, and e(x, y) for x eats y. The following sentences are all equivalent to each other except: Question options: -∀x v(x) <-> (∀y e(x, y) -> -m(y)) -∀x v(x) <-> (-(∃y m(y) ^ e(x, y))) -∀x (∃y m(y) ^ e(x, y)) <-> -v(x) -∀x (-(∀y m(y) -> -e(x, y))) <-> -v(x) -No exception, they are all equivalent

No exception, they are all equivalent

No one held for murder is given bail. Smith isn't held for murder. So... Question options: -Smith is given bail. -Smith isn't given bail. -Smith is innocent. -None of these validly follows.

None of these validly follows

Anyone who has just lost a lot of blood is likely to faint. No one who is likely to faint is a safe pilot. So... Question options: -Everyone who has just lost a lot of blood is a safe pilot. -No one who has just lost a lot of blood is a safe pilot. -All safe pilots have just lost a lot of blood. -None of these validly follows.

None of who has just a lot of blood is safe pilot

Search strategies differ in the order of node expansion. The strategy from breadth-first... -Operates on first in, first out -Operates on first in, last out -Expands the node with the lowest g(n) = distance from the start to n -Expands the node with the lowest h(n) = the estimate from n to the goal -Expands the node with the lowest f(n) = g(n) + h(n)

Operates on first in, first out

Search strategies differ in the order of node expansion. The strategy from depth-first... Question options: -Operates on first in, first out -Operates on first in, last out -Expands the node with the lowest g(n) = distance from the start to n -Expands the node with the lowest h(n) = the estimate from n to the goal -Expands the node with the lowest f(n) = g(n) + h(n)

Operates on first in, last out

What is the Environment? (Which ONE that best characterizes the environment) -Hospital -Patient -Doctors -Symptoms

Patient

A medical diagnosis system is being considered by a hospital. The hospital administrator is concerned about the cost of implementing such a system, but proponents of the system argue that it will improve patient heath. Doctors will enter symptoms through a keyboard. These symptoms will be compared to previous diagnoses and the predicted diagnosis and recommended treatment will be displayed on a screen. Perform a PEAS analysis on the diagnosis system. Which of the following would be a reasonable Performance measure? (Which of the below apply?) -Patient Health - Cost of implementing the system - Cost of recommended treatment - The number of doctors trained to use the system

Patient Health, Cost of recommended treatment

Actions include... (Which apply?) Question options: -Preconditions -Goal states -Add-list -Delete-list

Preconditions, Add-list and Delete-list

The arc-consistency approach... (Which apply?) Question options: -Requires a considerable amount of overhead. -Requires almost no overhead. -Can eliminate large parts of the state space. -Rarely offers any improvement compared to more general search strategies.

Requires a considerable amount of overhead & Can eliminate large parts of the state space

What are the Actuators? (Which apply?) -Keyboard -Patient -Screen -Doctors

Screen

Which of the following problems would be good targets for an intelligent agent incorporating A* search. Which apply? -Solving a Rubik Cube -Writing a poem -Finding a path from Stormwind to Ogrimmar -Playing chess

Solving a Rubik Cube and Finding a path from Stormwind to Orgrimmar

Some cave dwellers use fire. All who use fire have intelligence. So... Question options: -All who have intelligence use fire. -Some cave dwellers have intelligence. -All cave dwellers have intelligence. -None of these validly follows.

Some cave dwellers have intelligence.

Characterize P -> ((Q V R) -> P). -Unsatisfiable -Tautology -Satisfiable but not tautology -Not a propositional logic sentence -None of the above

Tautology

A min-max search on a large game tree requires an evaluation function. Which nodes are evaluated using this function? (Pick one) -The root -The leaves -The min-nodes -All of the above

The leaves

Which games would be appropriate targets for min-max? (Which apply) - Tic-Tac-Toe - Backgammon - Poker - Go - Solitaire - Chess

Tic-Tac-Toe, Go, & Chess

Image: https://tinyurl.com/yy5cfhdz What move should Max make? -To the left -To the right -Down the center -None of the above

To the left

Image: https://tinyurl.com/yy5cfhdz Using alpha-beta pruning, the search algorithm could have ignored node H and below.

True

Image: https://tinyurl.com/yy5cfhdz Using alpha-beta pruning, the search algorithm could have ignored node J and below.

True

True or False: A constraint satisfaction problem can be solved with a search algorithm.

True

True or False: Breadth-first search is a special case of Uniform-cost search.

True

True or False: Classical logic can only help in representing knowledge that is known to be true or false.

True

True or False: Consider an Intelligent Agent designed to solve cross word puzzles. This environment is fully observable (not partially).

True

True or False: Constraint propagation, of which Arc-consistency is an example, enforces constraints locally.

True

True or False: Forward checking can identify an unproductive branch of the search tree by keeping track of remaining legal values for unassigned variables.

True

True or False: Given the following knowledge base KB:... A <-> B ...the query -A V B is entailed by KB?

True

True or False: Goal-based agents often incorporate search strategies.

True

True or False: N-fold cross validation - a common technique for evaluating machine learning and artificial intelligence models -- builds n models, evaluates each instance exactly once and uses each instance as a training example exactly n-1 times.

True

True or False: Non-monotonic logics provide the means of retracting some of the conclusions we believed at an earlier stage.

True

True or False: One drawback of neural networks is that the models are difficult to interpret.

True

True or False: The drawback of breadth-first search is the space complexity, O(bd), and the drawback of depth-first search is that it is not guaranteed to find an optimal solution (or even a solution at all).

True

True or False: This environment is deterministic (not stochastic).

True

True or False: This environment is discrete (not continuous).

True

True or False: This environment is single-agent (not multi-agent).

True

True or False: This environment is static (not dynamic).

True

True or False: Utility-based agents choose actions that maximize its performance measure.

True

True or False: When mapping a real-world problem to a state space, the successor function links states together through abstractions of the agent's actuators.

True

True or False: ∀x P(x) <-> ~∃x ~P(x)

True

True or False: Artificial Intelligence is commonly taught through the use of Intelligent Agents. Agents (humans, robots, etc.) observe the world through precepts and act on the world through actuators. Internal to the agent is a function that maps precepts to actions.

True

True or False: Eliza engages in a "conversation" with a user by mimicking a psychotherapist. Her responses are generated by matching inputs to a set of rules.

True

Mycin... (Which apply?) Question options: -Was designed as an expert system for diagnosis and treatment of bacterial infections. It performs as well as the best medical experts in the field. -Relies on sentences that are labeled not with probabilities, but with certainty factors ranging from -1 to 1. -Uses a special (ad-hoc) form of Modus Ponens. -Labels instances based on probability theory. -Is able to combine evidence.

Was designed as an expert system for diagnosis and treatment of bacterial infections. It performs as well as the best medical experts in the field. Relies on sentences that are labeled not with probabilities, but with certainty factors ranging from -1 to 1. Uses a special (ad-hoc) form of Modus Ponens. Is able to combine evidence.

P(vomiting | flu) = .72 is an example of... Question options: -diagnostic inference -causal inference -intercausal inference -mixed inference

causal inference

P(speeding | ticket /\ runRedLight) = 0.0027 is an example of... Question options: -diagnostic inference -causal inference -intercausal inference -mixed inference

diagnostic inference

An inference method is complete if it... Question options: -produces only entailed sentences. -is able to produce every expression that is entailed by the KB. -is efficient in both time and space. -is a tautology.

is able to produce every expression that is entailed by the KB

An inference method is sound if it... Question options: -produces only entailed sentences. -it is able to produce every expression that is entailed by the KB. -is efficient in both time and space. -is a tautology.

produces only entailed sentences

An inference procedure... Question options: -is a declarative knowledge representation. -provides rules for deriving new facts from existing facts. -is a proof. -is a type of inheritance.

provides rules for deriving new facts from existing facts.

Consider the crossword puzzle given below: Image: https://tinyurl.com/y5pcosul Suppose we have the following words in our dictionary: ant, ape, big, bus, car, has, bard, book, buys, hold, lane, year, rank, browns, ginger, symbol, syntax. The goal is to fill the puzzle with words from the dictionary. The set of variables would be... -{1,2,3,4} -The set of words from the dictionary. {ant, ape, big ...} -{1 across, 3 across, 4 across, 1 down, 2 down} -The solution to the crossword puzzle.

{1 across, 3 across, 4 across, 1 down, 2 down}

The domain for 1 across is ... Image: https://tinyurl.com/y5pcosul Question options: -{ant, ape, big, bus, car, has, bard, book, buys, hold, lane, year, rank, browns, ginger, symbol, syntax} -{ant, ape} -{ant, ape, big, bus, car, has} -{big, bus, bard, book, buys, browns}

{ant, ape, big, bus, car, has}

Which one is the translation of "John has exactly one brother"? Question options: -∃x,y brother(John, x) ^ brother(John, y) ^ x = y -∃x brother(John, x) -> ∀y(brother(John, y) ^ x = y) -∃x brother(John, x) -> ∀y(brother(John, y) -> x = y) -∃x brother(John, x) ^ ∀y(brother(John, y) -> x = y) -∀x brother(John, x) -> ∃y(brother(John, y) ^ x = y)

∃x brother(John, x) ^ ∀y(brother(John, y) -> x = y)