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management and artificial intelligence

Questions and Answers of Management And Artificial Intelligence

Give an argument for and against each of these propositions, about the possibility of a singularity, when computers will be more intelligent than people.(a) The singularity will never occur as people
Find some current AI applications and classify the state-of-the-art for that application in terms of the dimensions. Does the application automate what Kahneman [2011] calls System 1 or System 2
Consider one of the following scenarios.(i) You are working for a company and have been asked about the feasibility of building a tool for predicting the results of an upcoming election so they can
For each leaf in the decision tree of Figure 19.1 (page 786) (starting with “use” or “do”), give an example of an application that has the characteristics that would end at that leaf. For
Consider the need for government legislation, regulation, and enforcement of restrictions on the use of AI. Give three reasons in favor of restrictions and three reasons against. Which, on balance,
Consider the proposal to require strong professional codes of ethics for AI designers and engineers. Give three reasons in favor of requiring such codes and three reasons against. Which, on balance,
Discuss how one of the normative ethical systems discussed (virtue, consequentialism, and deontological) could be used in design guidelines for an autonomous car.
Estimate and compare the energy use of deep learning systems and Bitcoin miners, globally. Compare your results to the energy use of a typical city.
Human rights and animal rights are well recognized. Outline a case for or against robot rights. Be specific about the robot rights you are discussing.
Consider the use of robots and companions for the elderly, the disabled, or infants. Investigate and describe briefly the current state of the art for these companions for one of those populations.
There have been proposals made for a global ban on the use of lethal autonomous weapon systems (LAWS). Investigate and describe the current status of action on a ban on the use of LAWS. Present a
Represent the electrical domain of previous chapters as a probabilistic logic program, so that it will run in AIPython (aipython.org) or Problog.The representation should include the probabilistic
Consider diagnosing the errors school students make when adding multi-digit numbers. Consider adding two multi-digit numbers to form a third multi-digit number, as in A1 A0+ B1 B0 C2 C1 C0 where Ai,
Suppose you have a relational probabilistic model for movie prediction, which represents P(likes(P, M) | age(P), genre(M))where age(P) and genre(M) are a priori independent(a) What is the treewidth
Consider Example 17.8 (page 748). Suppose that the motive for X to shoot Y is that they are being paid by someone else, Z, who needs to have motive to kill Y. Draw the corresponding plate model. (If
Suppose Boolean parameterized random variables young(Person)and cool(Item) are parents of Boolean buys(Person, Item). Suppose there are 3000 people and 200 items.(a) Draw this in plate notation.(b)
Change the stochastic gradient descent algorithm of Figure 17.2(page 739) that minimizes formula (17.1) so it adjusts the parameters, including regularization, after a batch of examples. How does the
An alternative regularization for collaborative filtering is to minimize∑u,i,r ∈D(r(u, i) − r)2 + λ(ib[i]2 + ub[u]2 + ∑p(ip[i, p]2 + up[u, p]2)).(a) How doe this differ from the
A variant of the gradient descent algorithm for collaborative filtering (Figure 17.2) can be used to predict P(rating > threshold) for various values of threshold in {1, 2, 3, 4}. Modify the code so
For the following, explain how each is categorized by the top-level ontology of Section 16.3.2 (page 723):(a) your skin(b) the period at the end of the first sentence of this chapter (c) the
A luxury hotel has multiple rooms to rent, each of which is comfortable and has a view. The hotel must also have more than one restaurant. There must be menu items for vegetarians and for meat eaters
Suppose a “beach resort” is a resort near a beach that the resort guests can use. The beach has to be near the sea or a lake, where swimming is permitted. A resort must have places to sleep and
Write an ontology for the objects that often appear on your desk that may be useful for a robot that is meant to tidy your desk. Think of the categories that (a) the robot can perceive and (b) should
Sam has proposed that any n-ary relation P(X1, X2, X3,..., Xn) can be re-expressed as n − 1 binary relations, namely P1(X1, X2), P2(X2, X3), P3(X3, X4),..., Pn−1(Xn−1, Xn).Explain to Sam why
Give 10 tuples that are related to the first goal scored in the 2010 FIFA World Cup Final (Q208401 in Wikidata), scored by Andres Iniesta (Q43729) ´at 116 minutes. Either draw the relationships as
Christine Sinclair (Q262802) was born in Burnaby (Q244025), British Columbia. Give the triples in Wikidata that relate her place of birth to the name of the province she was born in. The result
A travel site has a database that represents information about hotels and feedback from users that uses the relations hotel(Hotel Id, Name, City, Province or state, Country, Address)reported
There are many possible kinship relationships you could imagine, like mother, father, great-aunt, second-cousin-twice-removed, and naturalpaternal-uncle. Some of these can be defined in terms of the
Consider what would happen in Example 15.44 (page 693) if empty course had been defined as empty course(C) ← course(C) ∧ ∼enrolled(S,C).Suppose the rest of the knowledge base is course(cs422).
Construct a knowledge base and a dictionary based on Figure 15.12 (page 686) to answer geographical questions such as that given in Figure 1.3(page 13). For each query, either show how it can be
The extra arguments in a definite-clause grammar makes it strictly more powerful than a context-free grammar. The language {anbncn | n ≥ 0}, which consists of sentences that are made up of a number
In this question, you are to write a definite-clause knowledge base for the design of custom video presentations.Assume that the video is annotated using the relation segment(SegId,
The aim of this question is to get practice writing simple logic programs.(a) Write a relation remove(E, L,R) that is true if R is the list resulting from removing one instance of E from list L. The
Consider the following logic program:ap(emp, L, L).ap(c(H, T), L, c(H,R)) ← ap(T, L,R).adj(A, B, L) ← ap(F, c(A, c(B, E)), L).(a) Give a top-down derivation (including all substitutions) for one
Consider the following logic program:rd(cons(H, cons(H, T)), T).rd(cons(H, T), cons(H,R)) ← rd(T,R).Give a top-down derivation, showing all substitutions for the query ask rd(cons(a, cons(cons(a,
List all of the ground atomic logical consequences of the following knowledge base:q(Y) ← s(Y,Z) ∧ r(Z). p(X) ← q(f(X)). s(f(a), b).s(f(b), b). s(c, b). r(b).
For each of the following pairs of atoms, either give a most general unifier or explain why one does not exist:(a) p(X,Y,a, b, W) and p(E,c, F, G, F)(b) p(Y,a, b,Y) and p(c, F, G, F)(c) foo(Z, [a,
Give a most general unifier of the following pairs of expressions:(a) p(f(X), g(g(b))) and p(Z, g(Y))(b) g(f(X),r(X), t) and g(W,r(Q), Q)(c) bar(val(X, bb),Z) and bar(P, P)
What is the result of the following applications of substitutions?(a) f(A, X,Y, X,Y){A/X,Z/b,Y/c}.(b) yes(F, L) ← append(F, c(L, nil), c(l, c(i, c(s, c(t, nil))))){F/c(l, X1),Y1/c(L, nil),
Consider the following knowledge base:has access(X, library) ← student(X).has access(X, library) ← faculty(X).has access(X, library) ← has access(Y, library) ∧ parent(Y, X).has access(X,
Consider the following knowledge base:r(a). r(e). p(c).q(b). s(a, b). s(d, b).s(e, d). p(X) ← q(X) ∧ r(X). q(X) ← s(X,Y) ∧ q(Y).Show the set of ground atomic consequences derivable from this
Consider a domain with two individuals (✂ and ☎), two predicate symbols (p and q), and three constants (a,b, and c). The knowledge base KB is defined by p(X) ← q(X).q(a).(a) Give one
The stochastic policy iteration algorithm of Figure 14.10 (page 634)is based on SARSA (page 596)). How could it be modified to be off-policy as in Q-learning (page 590)? [Hint: Q-learning updates
Consider the following alternative ways to update the probability P in the stochastic policy iteration algorithm of Figure 14.10 (page 634).(i) Make more recent experiences have more weight by
In Example 14.12 (page 624), what is the Nash equilibrium with randomized strategies? What is the expected value for each agent in this equilibrium?
For the hawk–dove game of Example 14.11 (page 624), where D > 0 and R > 0, each agent is trying to maximize its utility. Is there a Nash equilibrium with a randomized strategy? What are the
Consider the game of Tic-Tac-Toe (also called noughts and crosses), which is played by two players, an “X” player and an “O” player who alternate putting their symbol in a blank space on a 3
Modify Figure 14.5 (page 617) to include nature moves. Test it on a (simple) perfect information game that includes randomized moves (e.g., coin toss or roll of a dice). Recall (page 612) that in an
In Example 13.6 (page 601), some of the features are perfectly correlated (e.g., F6 and F7). Does having such correlated features affect what functions are able to be represented? Does it help or
In SARSA with linear function approximation, using linear regression to minimize r + γQw(s, a) − Qw(s,a) gives a different algorithm than Figure 13.8 (page 602). Explain what you get and why what
The grid game of Example 13.6 (page 601) included features for the x-distance to the current treasure and are the y-distance to the current treasure.Chris thought that these were not useful as they
The model-based reinforcement learner allows for a different form of optimism in the face of uncertainty. The algorithm can be started with each state having a transition to a “nirvana” state,
Consider four different ways to derive the value of αk from k in Qlearning (note that for Q-learning with varying αk, there must be a different count k for each state–action pair).(i) Let αk =
For the following reinforcement learning algorithms:(i) Q-learning with fixed α and 80% exploitation.(ii) Q-learning with fixed αk = 1/k and 80% exploitation.(iii) Q-learning with αk = 1/k and
Compare the different parameter settings for Q-learning for the game of Example 13.2 (page 585) (the “monster game” in AIPython (aipython.org))In particular, compare the following situations:(i)
For the plot of the total reward as a function of time as in Figure 13.4(page 594), the minimum and zero crossing are only meaningful statistics when balancing positive and negative rewards is
Suppose a Q-learning agent, with fixed α and discount γ, was in state 34, did action 7, received reward 3, and ended up in state 65. What value(s)get updated? Give an expression for the new value.
Explain how Q-learning fits in with the agent architecture of Section 2.1.1 (page 53). Suppose that the Q-learning agent has discount factor γ, a step size of α, and is carrying out an -greedy
How can variable elimination for decision networks, shown in Figure 12.14 (page 546), be modified to include additive discounted rewards? That is, there can be multiple utility (reward) nodes, to be
In a decision network, suppose that there are multiple utility nodes, where the values must be added. This lets us represent a generalized additive utility function. How can the VE for decision
Consider the MDP of Example 12.31 (page 557).(a) As the discount varies between 0 and 1, how does the optimal policy change?Give an example of a discount that produces each different policy that can
Explain why we often use discounting of future rewards in MDPs.How would an agent act differently if the discount factor was 0.6 as opposed to 0.9?
What is the main difference between asynchronous value iteration and standard value iteration? Why does asynchronous value iteration often work better than standard value iteration?
Consider the following decision network:(a) What are the initial factors? (Give the variables in the scope of each factor, and specify any associated meaning of each factor.)(b) Give a legal
(page 455). When an alarm is observed, a decision is made whether or not to shut down the reactor.Shutting down the reactor has a cost cs associated with it (independent of whether the core was
Consider the belief network of
This exercise is to compare variable elimination and conditioning for the decision network of Example 12.16 (page 539).(a) For the inverse of the variable ordering for search used in Example
In Example 12.16 (page 539), suppose that the fire sensor was noisy in that it had a 20% false positive rate P(see smoke|report ∧ ¬smoke) = 0.2 and a 15% false negative rate P(see smoke|report ∧
How sensitive are the answers from the decision network of Example 12.16 (page 539) to the probabilities? Test the program with different conditional probabilities and see what effect this has on the
Suppose that, in a decision network, there were arcs from random variables “contaminated specimen” and “positive test” to the decision variable“discard sample.” You solved the decision
Suppose that, in a decision network, the decision variable Run has parents Look and See. Suppose you are using VE to find an optimal policy and, after eliminating all of the other variables, you are
Some students choose to cheat on exams, and instructors want to make sure that cheating does not pay. A rational model would specify that the decision of whether to cheat depends on the costs and the
Students have to make decisions about how much to study for each course. The aim of this question is to investigate how to use decision networks to help them make such decisions.Suppose students
One of the decisions we must make in real life is whether to accept an invitation even though we are not sure we can or want to go to an event. Figure 12.24 gives a decision network for such a
Consider the following two alternatives:(i) In addition to what you currently own, you have been given $1000. You are now asked to choose one of these options:50% chance to win $1000 or get $500 for
Prove that the completeness and/or transitivity axioms (page 519), imply the following statements. What axiom(s) do your proofs rely on?(a) o2 o1 is equivalent to o1 ! o2(b) if o1 ! o2 and o2 ! o3
Consider a two-variable causal network with Boolean variables A and B, where A is a parent of B, and the following conditional probabilities:P(a) = 0.2 P(b |a) = 0.9 P(b | ¬a) = 0.3.Consider the
Suppose someone provided the source code for a recursive conditioning (page 409) program that computes conditional probabilities in belief networks. Your job is to use it to build a program that also
Bickel et al. [1975] report on gender biases for graduate admissions at UC Berkeley. This example is based on that case, but the numbers are fictional.There are two departments, which we will call
Consider the causal network of Figure 11.12. The following can be answered intuitively or using the do-calculus. Explain your reasoning:(a) Does P(I | B) = P(I | do(B))?(b) Does P(I | G) = P(J |
Consider the causal network of Figure 11.12 (page 513). For each part, explain why the independence holds or doesn’t hold, using the definition of d-separation. The independence asked needs to hold
Exercise 9.2 (page 451) asked to intuitively explore independence in Figure 9.37. For parts (c), (d), and (e) of Exercise 9.2, express the question in terms of conditional independence, and use
Suppose Kim has a camper van (a mobile home) and likes to keep it at a comfortable temperature and noticed that the energy use depended on the elevation. Kim knows that the elevation affects the
Consider the code for decision trees in Example 10.7 (page 472), and the Bayesian information criteria (BIC) (page 473) for decision trees. Consider the three cases: the BIC, the decision tree code
To initialize the EM algorithm in Figure 10.8 (page 480) consider two alternatives:(a) allow P to return a random distribution the first time through the loop(b) initialize cc and fc to random
Suppose the k-means algorithm is run for an increasing sequence of values for k, and that it is run for a number of times for each k to find the assignment with a global minimum error. Is it possible
Consider the unsupervised data of Figure 10.5 (page 477).(a) How many different stable assignments of examples to classes does the kmeans algorithm find when k = 2? [Hint: Try running the algorithm
Suppose you have designed a help system based on Example 10.5(page 469) and much of the underlying system which the help pages are about has changed. You are now very unsure about which help pages
Consider the help system of Example 10.5 (page 469).(a) Using the c1 and wij counts in that example, give the probability of P(H | q), the distribution over help pages given q, the set of words in a
Consider designing a help system based on Example 10.5 (page 469).Discuss how your implementation can handle the following issues, and if it cannot, whether it is a major problem.(a) What should be
Try to construct an artificial example where a naive Bayes classifier can give divide-by-zero error in test cases when using empirical frequencies as probabilities. Specify the network and the
How well does particle filtering work for Example 9.48 (page 449)?Try to construct an example where Gibbs sampling works much better than particle filtering. [Hint: Consider unlikely observations
Which of the following algorithms suffers from underflow (real numbers that are too small to be represented using double precision floats): rejection sampling, importance sampling, particle
Consider the problem of filtering in HMMs (page 426).(a) Give a formula for the probability of some variable Xj given future and past observations. You can base this on Equation (9.6) (page 426).
Suppose Sam built a robot with five sensors and wanted to keep track of the location of the robot, and built a hidden Markov model (HMM) with the following structure (which repeats to the
Extend Example 9.30 (page 420) so that it includes the state of the animal, which is either sleeping, foraging, or agitated.If the animal is sleeping at any time, it does not make a noise, does not
(page 228).(a) Explain what knowledge (about physics and about students) a belief-network model requires.(b) What is the main advantage of using belief networks over using abductive diagnosis or
This exercise continues
In a nuclear research submarine, a sensor measures the temperature of the reactor core. An alarm is triggered (A = true) if the sensor reading is abnormally high (S = true), indicating an overheating
Explain how to extend VE to allow for more general observations and queries. In particular, answer the following:(a) How can the VE algorithm be extended to allow observations that are disjunctions

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