,Unnamed: 0,Chapter,Midterm,Model,Condition,Question,Answer,questionId
0,3974,chapter17_1,midterm_2,T5,Fewshot,What is a utility function depending on a sequence of states and actions rather than on a single state?,environment history,3974
1,4462,chapter5_1,midterm_1,T5,Best Condition - with Davinci,"The initial state, actions function and result function define what?",the game tree,4462
2,2750,chapter2_3,midterm_1,T5,BadSummary,What type of env does the agent don't worry about changes in the env while selecting an action?,static,2750
3,4831,chapter19_5,midterm_2,T5,Best Condition - with Davinci,What type of learning requires a teacher to provide the correct answer to a machine?,Supervised learning,4831
4,4829,chapter19_5,midterm_2,T5,Best Condition - with Davinci,What is one that can adapt its behavior based on its experience?,learning machine,4829
5,2180,chapter17_1,midterm_2,T5,GoodSummary,"If discount factor gamma is close to 1, what is it?",purely additive model,2180
6,6421,chapter_3_4_1,1st midterm,T5,From GPT-3 generated summary,When is breadth-first search appropriate?,when all actions have the same cost,6421
7,1176,chapter22_1,midterm_2,GPT3,Zero,"What is reinforcement learning?
",Reinforcement learning is an alternative to supervised learning.,1176
8,1293,slp_chapter4_1,midterm_2,GPT3,Zero,"What is naive bayes?
",Naive bayes is a probabilistic classifier that returns the class with the maximum posterior probability given the document.,1293
9,892,chapter19_4,midterm_2,GPT3,BadSummary,"What is the optimal fit hypothesis?
","The optimal fit hypothesis is the hypothesis that minimizes the error rate, measure this on the test set of examples.",892
10,5753,chapter_2_4_6,1st midterm,T5,From raw text,What does the problem generator suggest?,exploratory actions,5753
11,326,slp_chapter6_4,midterm_2,GPT3,Best Condition - with Davinci,"What is the dot product of the vectors and ?
",The dot product of the vectors and is,326
12,4677,chapter12_3,midterm_2,T5,Best Condition - with Davinci,What is the knowledge base from which answers to all questions can be derived?,full joint distribution,4677
13,726,slp_chapter6_12,midterm_2,GPT3,GoodSummary,"What is another common metric for extrinsic evaluation? 
",Another common metric for extrinsic evaluation is task completion accuracy.,726
14,1684,SLP_chapter3_3,midterm_2,GPT3,Fewshot,"What is sampling from a distribution?
",Sampling from a distribution chooses random points according to their likelihood.,1684
15,192,chapter19_5,midterm_2,GPT3,Best Condition - with Davinci,"What is supervised learning?
",Supervised learning requires a teacher to provide the correct ,192
16,5871,chapter_3_3_2,1st midterm,T5,From raw text,What is another name for FIFO queue?,first-in-first-out queue,5871
17,5106,chapter_2,1st midterm,GPT3,From raw text,"What is the nature of environments?
",The nature of environments is that they are diverse.,5106
18,5675,chapter_2_4_1,1st midterm,T5,From raw text,What are the four basic kinds of agent programs that embody the principles underlying almost all intelligent systems?,Simple reflex agents,5675
19,4599,chapter17_2,midterm_2,T5,Best Condition - with Davinci,For what state is the utility updated by the maximum of the actions that would make the utility equal to the actual utility?,each state,4599
20,6157,chapter_3_3_1,1st midterm,GPT3,From GPT-3 generated summary,"What is the first step of best-first search?
",The first step of best-first search is to choose a node on the frontier with the minimum value and expand it.,6157
21,6159,chapter_3_3_1,1st midterm,GPT3,From GPT-3 generated summary,"What is the third step of best-first search?
",The third step of best-first search,6159
22,2874,chapter7_5,midterm_1,T5,BadSummary,What means one is the negation of another?,Negate complementary literals with unit resolution,2874
23,3382,chapter22_4,midterm_2,T5,Zero,What is the evaluation function?,an approximate utility function,3382
24,6152,chapter_3_3,1st midterm,GPT3,From GPT-3 generated summary,"What is the advantage of using a search tree?
",Using a search tree is advantageous because it allows for the creation of a path between the start state and the goal state.,6152
25,646,slp_chapter5_1,midterm_2,GPT3,GoodSummary,"What is the advantage of naive bayes over logistic regression?
",The advantage of naive bayes over logistic regression is that naive bayes can work even better on very small data sets.,646
26,5115,chapter_2_2_2,1st midterm,GPT3,From raw text,"What is rational at any given time?
","Rationality depends on four things: the performance measure that defines the criterion of success, the agent",5115
27,6166,chapter_3_3_3,1st midterm,GPT3,From GPT-3 generated summary,"What is a redundant path?
",A redundant path is a path that is just a worse way to get to the same state.,6166
28,201,chapter19_6,midterm_2,GPT3,Best Condition - with Davinci,"What if y is 0 but hw(x) is 1?
",If y is 0 but hw(x) is then wi is decreased when the corresponding input xi is positive and increased when xi is negative.,201
29,1006,slp_chapter6_12,midterm_2,GPT3,BadSummary,"What is the dataset for the wordsim-3dataset?
",The dataset for the wordsim-3dataset is a commonly used set of ratings from 0 to for 3noun pairs.,1006
30,2087,chapter6_5,midterm_1,T5,GoodSummary,Doesn't need what?,backtracking,2087
31,4963,slp_chapter7_3,midterm_2,T5,Best Condition - with Davinci,How do hidden units represent the parameters for the entire hidden layer?,combining the weight vector and bias for each unit into a single weight matrix and a single bias vector,4963
32,1821,slp_chapter7_1,midterm_2,GPT3,Fewshot,"What is the sigmoid function?
",The sigmoid function is a standard non-linearity that maps values from –∞ to +∞ to values between 0 and 1.,1821
33,386,chapter3_3,midterm_1,GPT3,GoodSummary,"What is a search algorithm?
",A search algorithm is a set of rules that map from search problems to solutions or an indication of failure.,386
34,1647,chapter12_1,midterm_2,GPT3,Fewshot,"What are the drawbacks of using a correct contigent plan?
",The drawbacks of using a correct contigent plan are that it can grow arbitrarily large and sometimes no plan is guaranteed to achieve the goal.,1647
35,1475,chapter2_4,midterm_1,GPT3,Fewshot,"What is ai?
",Ai is the study of how to create an artificial agent that can act rationally.,1475
36,6446,chapter_3_4_3,1st midterm,T5,From GPT-3 generated summary,Why is depth-first search still used in many areas of AI?,because it has much smaller memory requirements,6446
37,4316,slp_chapter6_11,midterm_2,T5,Fewshot,What reflect the statistics of their input and amplify bias?,Embeddings,4316
38,1517,chapter5_3,midterm_1,GPT3,Fewshot,"What is the value of the highest value choice we have found so far at any action point for max?
",The value of the highest value choice we have found so far at any action point for max is alpha.,1517
39,2274,chapter22_4,midterm_2,T5,GoodSummary,What does Hierarchical learning utilize?,joint state space,2274
40,937,slp_chapter4_8,midterm_2,GPT3,BadSummary,"What is the difference between linear and non-linear neural networks?
",The main difference between linear and non-linear neural,937
41,6313,chapter_2_2_3,1st midterm,T5,From GPT-3 generated summary,Does our definition of rationality say that it’s now OK to cross the road?,Far from it,6313
42,27,chapter6_5,midterm_1,GPT3,Best Condition - with Davinci,"How does cutset conditioning take o(d^c (n-c)d^time?
",Cutset conditioning takes o(d^c (n-c)d^time by first solving the tree until it is consistent overall and then removing the cycle cutset if it has size c.,27
43,2066,chapter6_3,midterm_1,T5,GoodSummary,What does the least-constarining-value heuristic rule out for its neighbors?,fewest possibilities,2066
44,65,chapter16_2,midterm_2,GPT3,Best Condition - with Davinci,"What is decomposability?
",Decomposability is the constraint on rational preferences that requires that preferences be decomposable.,65
45,5596,chapter_2_3_2,1st midterm,T5,From raw text,How do we illustrate the ideas?,analyze several task environments,5596
46,6008,chapter_1_1,1st midterm,GPT3,From GPT-3 generated summary,"What are the strengths and weaknesses of each of these methods?
","The different approaches use different methods, and have both strengths and weaknesses.",6008
47,2515,slp_chapter4_7,midterm_2,T5,GoodSummary,What do we compute in microaveraging?,precision and recall,2515
48,697,slp_chapter6_2,midterm_2,GPT3,GoodSummary,"What are vectors for representing words called?
",Vectors for representing words are called embeddings.,697
49,2145,chapter7_5,midterm_1,T5,GoodSummary,Forward chaining is sound: every inference is essentially an appli- cation of what?,Modus Ponens,2145
50,1319,slp_chapter4_7,midterm_2,GPT3,Zero,"How can we build a confusion matrix for visualizing how an algorithm performs with respect to human gold labels?
",We can build a confusion matrix for visualizing how an algorithm performs with respect to human gold labels by labeling each cell as positive outcomes.,1319
51,4350,chapter27_1,midterm_1,T5,Best Condition - with Davinci,"Whose ""argument from informality of behavior"" posits that human behavior is too complex to be captured by any formal set of",Turing,4350
52,6054,chapter_27_1_4,1st midterm,GPT3,From GPT-3 generated summary,"What is the threshold for a program to pass the test?
","If the interrogator is fooled 3of the time, the program passes the test.",6054
53,4721,SLP_chapter3_2,midterm_2,T5,Best Condition - with Davinci,What is the inverse probability of a language model on a test set called?,PP,4721
54,1175,chapter17_3,midterm_2,GPT3,Zero,"What is the optimal policy maximized?
",The optimal,1175
55,2011,chapter5_2,midterm_1,T5,GoodSummary,What can we use to cache the heuristic values of states?,a transposition table,2011
56,1108,chapter6_4,midterm_1,GPT3,Zero,"What is min conflict?
",Min conflict is a popular local search method that works by selecting the value for a variable that results in the minimum number of conflicts with other variables.,1108
57,753,chapter3_4,midterm_1,GPT3,BadSummary,"What is ucs?
",Ucs is a search algorithm that uses a priority queue.,753
58,769,chapter5_2,midterm_1,GPT3,BadSummary,"Can the minmax algorithm be extended to multiplayer games?
","Yes, the minmax algorithm can be extended to multiplayer games by making each node a vector of values.",769
59,5208,chapter_3_3_4,1st midterm,GPT3,From raw text,"1
",To,5208
60,6069,chapter_2,1st midterm,GPT3,From GPT-3 generated summary,"What is a perfect agent?
",A perfect agent is an agent that behaves optimally in every environment and cannot be defeated.,6069
61,210,slp_chapter4_3,midterm_2,GPT3,Best Condition - with Davinci,"What is the disadvantage of concatenating the documents into a single document?
",The disadvantage of concatenating the documents into a single document is that it may result in duplicate words in the single document.,210
62,5175,chapter_3_3_1,1st midterm,GPT3,From raw text,"What does best-first search do on each iteration?
","On each iteration, best-first search chooses a node on the frontier with minimum value, and returns it if its state is a goal state.",5175
63,3137,chapter27_1,midterm_1,T5,Zero,What is GOFAI?,Good Old-Fashioned AI,3137
64,4447,chapter3_5,midterm_1,T5,Best Condition - with Davinci,What is optimal in a finite environment?,The complete approach,4447
65,5874,chapter_3_3_2,1st midterm,T5,From raw text,What is another name for a lookup table?,a hash table,5874
66,5217,chapter_3_4_1,1st midterm,GPT3,From raw text,"What is a complete search strategy?
",A complete search strategy is a search strategy that finds all possible solutions to a problem.,5217
67,5714,chapter_2_4_5,1st midterm,T5,From raw text,What should a more general performance measure allow a comparison of different world states according to?,how happy they would make the agent,5714
68,5067,chapter_27_1,1st midterm,GPT3,From raw text,"What is human-level ai?
","Human-level ai is also called ""general ai"" or ""strong ai""—programs that can solve an arbitrarily wide variety of tasks, including novel ones, and do so as well as a human.",5067
69,706,slp_chapter6_4,midterm_2,GPT3,GoodSummary,"What is the problem with the raw dot product?
",The raw dot product favors long vectors.,706
70,3896,chapter16_3,midterm_1,T5,Fewshot,What type of utility curves are risk seeking?,convex utility curves,3896
71,4322,slp_chapter6_11,midterm_2,T5,Fewshot,What is a harm caused by a system demeaning or even ignoring some social groups?,Representational harm,4322
72,3492,chapter19_1,midterm_2,T5,Zero,What is the most common type of unsupervised learning?,clustering,3492
73,1598,chapter7_5,midterm_1,GPT3,Fewshot,"
","
",1598
74,1501,chapter3_6,midterm_1,GPT3,Fewshot,"What is the straight line/euclidean distance heuristic?
",The straight line/euclidean distance heuristic is a heuristic that uses the straight line distance between two states to estimate the cost of moving between the states.,1501
75,2962,SLP_chapter3_4,midterm_2,T5,BadSummary,What is converted to the unknown word token in a text normalization step?,any word that is not in this set,2962
76,3395,chapter12_1,midterm_2,T5,Zero,What can be used to summarize the uncertainty that comes from an agent's laziness and ignorance?,probability theory,3395
77,156,chapter13_1,midterm_2,GPT3,Best Condition - with Davinci,"What is a dag?
",A dag is a directed acyclic graph.,156
78,611,slp_chapter4_1,midterm_2,GPT3,GoodSummary,"What is a discriminative classifier?
",A discriminative classifier is a classifier that instead learns what features from the input are most useful to discriminate between the different possible classes.,611
79,5940,chapter_3_4_1,1st midterm,T5,From raw text,What is scary about time and space complexity?,Exponential bounds,5940
80,3066,slp_chapter9_1,midterm_2,T5,BadSummary,What type of models tend to have much higher predictive accuracy than n-gram LMs?,Neural LMs,3066
81,6162,chapter_3_3_2,1st midterm,GPT3,From GPT-3 generated summary,"What are the reached states stored in?
",The reached states are stored in a lookup table.,6162
82,2973,chapter13_1,midterm_2,T5,BadSummary,What connects pairs of nodes?,Directed links or arrows,2973
83,6450,chapter_3_4_5,1st midterm,T5,From GPT-3 generated summary,What is an algorithm that starts at an initial state and searches forward and backwards simultaneously in the hope that the two searches will meet?,Bidirectional search,6450
84,6262,chapter_27_2_1,1st midterm,T5,From GPT-3 generated summary,What does John Searle argue about the human in his famous Chinese room argument?,does not understand Chinese,6262
85,605,chapter19_6,midterm_2,GPT3,GoodSummary,"What is convergence of stochastic gradient descent not guaranteed?
",Convergence of stochastic gradient descent is not guaranteed.,605
86,5627,chapter_2_3_2,1st midterm,T5,From raw text,In what type of environment could the current decision affect all future decisions?,sequential environments,5627
87,1257,chapter13_2,midterm_2,GPT3,Zero,"What is the chain rule?
","The chain rule is used to define a generic entry in the joint distribution as follows: p(xx..., xn) = ∏^n_(i=1)θ(x_i | parents(x_i)).",1257
88,3597,slp_chapter5_1,midterm_2,T5,Zero,What does logistic regression work by first training a model on?,training data,3597
89,812,chapter7_3,midterm_1,GPT3,BadSummary,"What is a model?
",A model is a set of possible worlds in which a sentence is true.,812
90,3506,chapter19_3,midterm_2,T5,Zero,Decision trees can generate error or noise in the data if the results are what?,nondeterministic,3506
91,5056,chapter_1_1_4,1st midterm,GPT3,From raw text,"What is the standard model of ai?
",The standard model of ai is the study and construction of agents that do the right thing.,5056
92,2371,chapter13_2,midterm_2,T5,GoodSummary,What is important to remember when constructing a Bayesiant network?,stick to causal model,2371
93,2732,chapter2_2,midterm_1,T5,BadSummary,"What does right thing, but what is right thing?",Rational agent,2732
94,5182,chapter_3_3_2,1st midterm,GPT3,From raw text,"What is the path-cost of the node?
","The path-cost of the node is the total cost of the path from the initial state to this node. in mathematical formulas, we use as a synonym for path-cost.",5182
95,6218,chapter_1_1_3,1st midterm,T5,From GPT-3 generated summary,What is the study of irrefutable thinking called?,logic,6218
96,4133,chapter19_2,midterm_2,T5,Fewshot,What is the amount of change in the hypothesis due to fluctuations in the training data?,Variance,4133
97,6458,chapter_3_4_6,1st midterm,T5,From GPT-3 generated summary,Breadth-first search expands nodes in order of increasing depth from the root.,the root is expanded first,6458
98,94,chapter22_4,midterm_2,GPT3,Best Condition - with Davinci,"What is the evaluation function?
",The evaluation function is a compact measure of desirability for potentially vast state spaces.,94
99,4166,slp_chapter4_1,midterm_2,T5,Fewshot,What is the process of using Bayes' rule to transform into other probabilities that have some useful properties?,Bayesian inference,4166
100,3,chapter16_3,midterm_1,GPT3,Best Condition - with Davinci,"What is a tradeoff?

",A tradeoff is looking at the utility of an object and the standard lottery and adjusting it until the agent is indifferent between the two.,3
101,693,slp_chapter9_3,midterm_2,GPT3,GoodSummary,"What is the loss function used for training an rnn?
",The loss function used for training an rnn is cross-entropy.,693
102,3323,chapter7_4,midterm_1,T5,Zero,What is a formal system that defines the allowable atomic sentences that can be used to construct complex sentences?,Propositional logic,3323
103,2502,slp_chapter4_4,midterm_2,T5,GoodSummary,What is a second important addition commonly made?,negation,2502
104,5527,chapter_2_2,1st midterm,T5,From raw text,How many agents can achieve the same average cleanliness?,two different agents,5527
105,5795,chapter_3_1,1st midterm,T5,From raw text,What does the agent want to do?,"take in the sights, improve its Romanian, enjoy the nightlife, avoid hangovers, and so on",5795
106,6415,chapter_3_3_4,1st midterm,T5,From GPT-3 generated summary,What are the four ways in which one can measure the performance of an algorithm?,"completeness, cost optimality, time complexity, and space complexity",6415
107,1333,slp_chapter4_10,midterm_2,GPT3,Zero,"What are the negative consequences of representational harms?
","Representational harms can have a number of negative consequences for those who experience them. they can lead to feelings of devaluation, isolation, and powerlessness. they can also make it harder for members of marginalized groups to access the resources they need to thrive.",1333
108,6374,chapter_3,1st midterm,T5,From GPT-3 generated summary,How is an agent a problem-solving agent?,if it needs to consider a sequence of actions to find its goal state,6374
109,953,slp_chapter7_1,midterm_2,GPT3,BadSummary,"What is a neural network?
",A neural network is a network of small computing units.,953
110,4051,chapter12_6,midterm_2,T5,Fewshot,What is a common pattern in which a single cause directly influences a number of effects called?,naive Bayes model,4051
111,3111,slp_chapter6_11,midterm_2,T5,BadSummary,What do embeddings encode that are a property of human reasoning?,implicit associations,3111
112,3534,chapter19_5,midterm_2,T5,Zero,Why should one branch out in one direction in order to test the PAC hypothesis?,reduce the number of false positives and false negatives,3534
113,909,slp_chapter4_3,midterm_2,GPT3,BadSummary,"How does the duplicate word removal algorithm work?
","For each doc, remove all duplicate words before you concatenate them into
a single document.",909
114,78,chapter17_3,midterm_2,GPT3,Best Condition - with Davinci,"What is the formal model of the multi-armed bandit problem?
",The multi-armed bandit problem is a specific class of sequential decision problems.,78
115,6358,chapter_2_4_6,1st midterm,T5,From GPT-3 generated summary,What can be constructed to improve every part of the agent?,learning mechanisms,6358
116,6156,chapter_3_3_1,1st midterm,GPT3,From GPT-3 generated summary,"What is the algorithm's primary question?
",The algorithm's primary,6156
117,6144,chapter_3_1_1,1st midterm,GPT3,From GPT-3 generated summary,"What is the state space represented as?
",The state space can be represented as a graph in which the vertices are states and the directed edges between them are actions.,6144
118,2844,chapter6_2,midterm_1,T5,BadSummary,What does AC-3 pop out?,"arbitrary arc $(X_i, X_j)$",2844
119,5083,chapter_27_1_3,1st midterm,GPT3,From raw text,"Who were the two people who proved the incompleteness theorem?
",The two people who proved the incompleteness theorem were gödel and turing.,5083
120,3463,chapter13_1,midterm_2,T5,Zero,What does each node correspond to?,random variable,3463
121,1924,chapter2_1,midterm_1,T5,GoodSummary,What is a function that maps a series of percepts to a series of actions called?,agent function,1924
122,4540,chapter6_5,midterm_1,T5,Best Condition - with Davinci,What cannot appear in two nodes of the tree if they are not connected by a constraint in the problem?,The same variable,4540
123,2827,chapter5_3,midterm_1,T5,BadSummary,What is the evaulation function for the min max value?,an herustic,2827
124,4002,chapter22_1,midterm_2,T5,Fewshot,What type of reinforcement learning does the agent not have a transition model?,model-free reinforcement learning,4002
125,5109,chapter_2_1,1st midterm,GPT3,From raw text,"2.what is an agent?
",2.an agent is anything that can be viewed as perce,5109
126,3412,chapter12_3,midterm_2,T5,Zero,What are useful rules for different derivations involving probability expressions?,Marginalization and conditioning,3412
127,447,chapter6_3,midterm_1,GPT3,GoodSummary,"What is the difference between commutativity and the order not mattering in csps?
","The difference between commutativity and the order not mattering in csps is that commutativity means that the order does not matter, and the order not mattering means that the order does not matter.",447
128,1859,slp_chapter6_2,midterm_2,GPT3,Fewshot,"What is a word vector space?
",A word vector space is a lexical space where words are represented as points.,1859
129,1188,chapter22_3,midterm_2,GPT3,Zero,"What should the agent tradeoff between exploitation of the current best action to maximize short-term reward and exploration of previously unknown states to gain information that might change the policy?
",The agent should tradeoff between exploitation of the current best action to maximize short-term reward and exploration of previously unknown states to gain information that might change the policy.,1188
130,1212,chapter12_6,midterm_2,GPT3,Zero,"What is a naive bayes model?
","A naive bayes model is a commonly occurring pattern in which a single cause directly influences a number of effects, all of which are conditionally independent, given the cause.",1212
131,2819,chapter3_6,midterm_1,T5,BadSummary,Which heuristic is more efficient than h1?,h2,2819
132,1858,slp_chapter6_2,midterm_2,GPT3,Fewshot,"What is a lexical space?
",A lexical space is a multi-dimensional space where words are represented as points.,1858
133,1566,chapter6_5,midterm_1,GPT3,Fewshot,"What is the time complexity of cutset conditioning?
","Cutset conditioning is a way of removing and assigning a set of values (""s"") such that the remaining tree is consistent. this can be done in o(nd^time.",1566
134,4285,slp_chapter9_3,midterm_2,T5,Fewshot,How can you get dense vectors?,train a classifier,4285
135,498,chapter17_2,midterm_2,GPT3,GoodSummary,"What is monte carlo planning?
",Monte carlo planning is a decision making algorithm that uses approximate solutions to find optimal policies online.,498
136,4142,chapter19_3,midterm_2,T5,Fewshot,The importance of an attribute is measured by what?,entropy,4142
137,1332,slp_chapter4_10,midterm_2,GPT3,Zero,"How can representational harms occur?
","Representational harms can occur in a number of ways, such as through the use of stereotypes, the exclusion of certain groups from opportunities or resources, or the provision of inferior services to groups that are already disadvantaged.",1332
138,878,chapter19_2,midterm_2,GPT3,BadSummary,"What is a model class?
",A model class is a set of all possible models that could be drawn from a hypothesis space.,878
139,856,SLP_chapter3_5,midterm_2,GPT3,BadSummary,"What is the difference between smoothing and discounting?
","Smoothing adds one to all n-gram counts before normalizing them into probabilities, whereas discounting lowers some non-zero counts in order to get probability mass that is assigned to zero counts.",856
