Artificial Intelligence 1 Final
Assume you have the following logic statement: ((Smoke ∧Heat) ⇒Fire)⟺ ((Smoke ⇒Fire)∨(Heat ⇒Fire)) This statement can be characterized as:
Valid
Assume you have the following logic statement: (Smoke ⇒Fire)⇒((Smoke ∧Heat)⇒Fire) This statement can be characterized as:
Valid
Assume you have the following logic statement: Big ∨ Dumb ∨ (Big ⇒ Dumb) This statement can be characterized as:
Valid
Assume you have the following logic statement: Smoke => Smoke This statement can be characterized as:
Valid
A logical expression that refers to an object in first-order predicate calculus is called a
term
Assume P(a)=0.3, P(b|a)=0.2, and P(c|a,b)=0.1. What is the value of P(a,b,c) ?
0.006
If a search algorithm has an effective branching factor of 1.5 and the solution depth is 5, then approximately how many nodes does it generate during the search?
20
If the minimax algorithm with alpha-beta pruning is used to find the optimal strategy for this game, then how many times will a pruning be performed?
4
If there are four binary variables in a probabilistic model, but two of them are independent of the rest, then what is the minimum number of values required to represent the model?
5
Given the full joint distribution shown above, calculate P(Tootchache | cavity).
<0.6, 0.4>
What statement best describes the role that machine learning plays in developing evaluation functions for use in the minimax search?
Allows to learn the form and parameters of the function from simulated or historical games.
The PEAS (Performance measures, Environment, Actuators, and Sensors) description of a task environment do NOT include which of the following?
Cost, Agent Physical Characteristics,
A Skolem constant is used in which of the following?
Existential instantiation
The problem of not knowing whether to make use of learned knowledge or continue learning in an online environment is called the:
Exploration vs. exploitation problem
A single perceptron has a larger hypothesis function space than a decision tree.
False
Which of the following is NOT an example of an ensemble machine learning method?
K'th Nearest Neighbor
What is the order in which nodes are examined when executing the A* search algorithm from Lugoj to Bucharest? (map and heuristic cost to Bucharest are given below)
Lugoj, Mehadia, Drobeta, Craiova, Timisoara, Pitesti, Bucharest
Which of the following heuristics picks variables with fewest legal values first?
Minimum-remaining-values heuristic
Assume you have the data set given below, which provides hypothetical examples of instances when people did or did not get hired for a job. It consists of three categorical attributes and a label that indicates "hired" or "not hired". Which attribute would be chosen as the root of the decision tree if the tree is induced using in a greedy manner using information gain as the criterion?
Opinions of References
What is the order in which nodes are examined when executing the Greedy search algorithm from Oradea to Bucharest? (map and heuristic cost to Bucharest are given below)
Oradea, Sibiu, Fagaras, Bucharest
If you perform simulated annealing with the temperature parameter kept at infinity at all times, then the algorithm is equivalent to which of the following?
Random walk
The following heuristic values to destination D are given: S: 12A: 8B: 6C: 9D: 0G: infinity What is order in which nodes are examined?
S, A, B, D
Which of the following properties best characterize the task environment of "Photographing tennis games. Specifically, choosing the moment for capturing a photo" ?
Single-agent Full Observable Continuous Static
Which of the following properties best characterize the task environment of "Playing Soccer" ? Episodic Single-agent Stochastic Deterministic Partially observable Continuous Fully observable Dynamic Sequential Discrete Multi-agent Static
Stochastic Partially Observable Continuous Dynamic Sequential Multi-agent
What is the purpose of an evaluation function when using a minimax search?
To cutoff search at some point and evaluate the likely payoff from that point
A CSP problem that is made strongly n-consistent can be solved in polynomial time complexity.
True
Bayesian networks cannot contain cycles.
True
Every First-Order Logic statement can be propositionalized so as to preserve entailment.
True
Every search problem with a partially observable environment can be solved by transforming it into one that is fully observable.
True
If a classifier has a recall performance of one, and the number of true positives is greater than zero, then the number of false negatives is:
Zero
Given the full joint distribution shown above, calculate P(toothache).
0.2
Consider the following situation. After your yearly checkup, the doctor has bad news and good news. The bad news is that you tested positive for a serious disease and that the test is 99% accurate (i.e. the probability of testing positive, when you do have the disease is 0.99 as is the probability of testing negative when you don't have the disease). The good news is that this is a rare disease, striking only 1 in 10,000 people of your age.
1%
Which of the following are needed for a complete search problem formulation? Actions Path Cost Search Algorithm Goal Test Transition Model Initial State
1. Initial State 2. Possible Actions 3. Transitional Model 4. Goal Test 5. Path Cost
What is the value of the F1 measure? Actual\Predicted POSITIVE 15/0 NEGATIVE 5/1
6/7 F Measure= precision x recall / precision + recall Precision = TP / TP + FP Recall = TP/ TP + FN
Which of the following search algorithms is NOT optimal?
Depth-first search
Which of the following properties best characterize the task environment of "Choosing to bid for a foreclosed house that you cannot see inside" ?
Discrete Multi-agent Static Partially Observable
Which of the following property is NOT required by database semantics:
Domain closure Closed-world assumption Unique-names assumption -----All are required
Assume you designed an email spam filter that detects whether an incoming email should be put into a spam folder (positive case). If the filter has high precision, but low recall, then what will be the effect?
Emails that end up in the spam folder will very likely be actual spam, but not many actual spam emails get detected.
An admissible heuristic is always consistent.
False
Conformant problems are search problems that are unsolvable.
False
If the solutions of a CSP are sparsely populated within the search landscape, then a local search algorithm will be faster than inference with backtracking search.
False
In machine learning, if a hypothesis function is inconsistent with the target function, then it disagrees with the target function on all examples.
False
The probability of a disjunction of two events is the sum of their individual probabilities.
False
Omniscience is a sufficient condition for rationality.
False - the definition of rational is making a logical decision with limited information Omniscience means all knowing
Bidirectional search has both better time and space complexity than breadth-first search. Both are complete and optimal. Therefore, bidirectional search should always be used instead of breadth-first search.
False- Bidirectional search is only complete and optimal if BFS is used and paths have uniform cost
If you perform simulated annealing with the temperature parameter kept at zero at all times, then the algorithm is equivalent to which of the following (disregard the termination check, i.e. "if T=0 then return current") ?
First-Choice Hill Climbing
Which of the following does NOT deal with uncertainty of events? Fudge factors Probability theory Fuzzy logic Default logic
Fuzzy Logic
Which English statement is closest to the meaning of the following logic statement? ∀x,y,l Person(x)∧Person(y)∧Language(l)∧Speaks(x,l)∧Speaks(y,l)⇒Understands(x,y)∧Understands(y,x).
If two people speak the same language, they will understand each other
What is a Turing Test?
It is a test used to determine computer's intelligence. It involves having a human decide whether it is communicating with a computer or a human being.
Consider the following game tree: What is the optimal strategy for this game using the minimax algorithm?
MAX: right, MIN: left, MAX: left, MIN: right
If a person works hard, then she will pass the AI course. Jennifer works hard. Therefore, Jennifer will pass the AI course. This is an example of an application of which of the following logical rules?
Modus Ponens
Assume you have the following logic statement: (Smoke⇒Fire) ⇒ (¬Smoke⇒¬Fire) This statement can be characterized as:
Neither valid or unsatisfiable
The set of all atomic events is called the:
Sample Space
What happens when the value k in the k'th nearest neighbor algorithm is increased?
The learning is more generalizible, but there will be more variance in the errors.
The goal of the vacuum world is to get to a state with no dirt in it (shown by dots in the squares of the states). If the initial state is the middle one (belief state of all physical states), then what is the maximum number of moves needed before the agent gets to the goal?
The problem has no solution
In a Bayesian Network with only binary variables, if each variable has no more than 5 parents, then the space complexity is linear in the number of variables.
True
The resolution algorithm can only be used if the KB is in Conjunctive Normal Form.
True
When an answer is certain, the entropy of the question is zero.
True
In breadth-first search, nodes on the frontier are examined in first-in, first-out fashion.
True- expands the shallowest nodes first
In depth-first search, nodes on the frontier are examined in last-in, first-out fashion.
True- opposite of breadth first search
If someone is a king then they have a crown. John is a king, so John has a crown. This is an example of
Universal instantiation
What is the unification of the following statements? p is Likes(John, x) q is Likes(y, Mary)
{x/Mary, y/John}
Which of the following first logic statements is equivalent to "Every student who gets an A in the 70-470 course gets a job or goes to graduate school."
∀s [Student(s)∧Grade(s,A,70470)⇒GetsJob(s)∨GoesToGradSchool(s)
Which of the following first logic statements is equivalent to "For every recursive solution, there is an iterative solution."
∀x ∃y [RecursiveSolution(x)⇒IterativeSolution(y)]
