,Unnamed: 0,Chapter,Midterm,Model,Condition,Question,Answer,questionId
0,3714,slp_chapter6_12,midterm_2,T5,Zero,The extrinsic evaluation metric for vector models is testing their performance on what?,NLP tasks,3714
1,1289,chapter19_6,midterm_2,GPT3,Zero,"If the perceptron produces the correct output, then what happens to the weights?
","If the perceptron produces the correct output, then the weights are not changed.",1289
2,5731,chapter_2_4_6,1st midterm,T5,From raw text,Who proposed building learning machines and then teaching them?,Turing,5731
3,6035,chapter_27_1,1st midterm,GPT3,From GPT-3 generated summary,"What is the difference between weak ai and strong ai?
","Weak ai is the idea that machines can act as if they were intelligent, while strong ai is the assertion that machines that do so are actually conscious and thinking.",6035
4,9,chapter6_1,midterm_1,GPT3,Best Condition - with Davinci,"What is the process of enforcing local consistency in each part of the constraint graph?
",The process of enforcing local consistency in each part of the constraint graph causes inconsistent values to be eliminated throughout the graph.,9
5,6110,chapter_2_4,1st midterm,GPT3,From GPT-3 generated summary,"What is a sensor?
",A sensor is a component that takes in percepts from the environment.,6110
6,3168,chapter2_3,midterm_1,T5,Zero,What is one in which there are multiple agents?,multiagent environment,3168
7,1249,chapter13_1,midterm_2,GPT3,Zero,"What is a parent of a node?
",A node is a parent of another node if there is an arrow from the former to the latter.,1249
8,5952,chapter_3_4_3,1st midterm,T5,From raw text,What could be implemented as a call to where the evaluation function is the negative of the depth?,BEST-FIRST-SEARCH,5952
9,3187,chapter3_1,midterm_1,T5,Zero,What is useful if it is possible to carry out each of the actions in the solution without additional solving?,An abstraction,3187
10,2202,chapter17_2,midterm_2,T5,GoodSummary,What is the generally most efficient for small state spaces?,policy evaluation using exact solution methods,2202
11,2941,SLP_chapter3_1,midterm_2,T5,BadSummary,What assumption is used to compute joint probability?,Markovian assumption,2941
12,2516,slp_chapter4_7,midterm_2,T5,GoodSummary,What better reflects the statistics of the smaller classes?,macroaverage,2516
13,2405,chapter13_3,midterm_2,T5,GoodSummary,"If Bayes net inference is competitive with and someties superior to exact algorithms on networks with large tree width, what is the best description?",computing,2405
14,6066,chapter_27_2_2,1st midterm,GPT3,From GPT-3 generated summary,"How is the problem of consciousness difficult to solve?
",The problem of consciousness is difficult to solve because it is ill-defined.,6066
15,1229,SLP_chapter3_2,midterm_2,GPT3,Zero,"What does a lower perplexity indicate?
",A lower perplexity indicates a better fit to the data.,1229
16,89,chapter22_2,midterm_2,GPT3,Best Condition - with Davinci,"What is the difference between the modified policy iteration approach and passive adaptive dynamic programming?
","The main difference between the modified policy iteration approach and passive adaptive dynamic programming is that the modified policy iteration approach uses the expected utilities of the successor states to calculate the total reward, while passive adaptive dynamic programming uses the learned reward function r and the model p to calculate the utilities of states.",89
17,1301,slp_chapter4_3,midterm_2,GPT3,Zero,"What is the difference between a naive bayes classifier and a maximum entropy classifier?
","A naive bayes classifier is a classifier that assumes that the features are conditionally independent given the class, while a maximum entropy classifier is a classifier that assumes that the features are conditionally dependent given the class.",1301
18,473,chapter7_5,midterm_1,GPT3,GoodSummary,"What is the deduction theorem?
","For any sentences α and β, α |= β if and only if the sentence (α ⇒ β) is valid.",473
19,3486,chapter19_1,midterm_2,T5,Zero,What is going from a specific set of observations to a general rule?,Induction,3486
20,4002,chapter22_1,midterm_2,T5,Fewshot,What type of reinforcement learning does the agent not have a transition model?,model-free reinforcement learning,4002
21,4197,slp_chapter4_9,midterm_2,T5,Fewshot,"If the?? we saw has a probability that is what, we reject the null hypothesis?",below the threshold,4197
22,632,slp_chapter4_7,midterm_2,GPT3,GoodSummary,"What is the macroaverage of class 1 and class 2?
",The macroaverage of class 1 and class 2 is 1.,632
23,4130,chapter19_2,midterm_2,T5,Fewshot,How does a test set generalize well?,if it accurately predicts the outcomes of the test set,4130
24,5183,chapter_3_3_3,1st midterm,GPT3,From raw text,"3.3.what is a repeated state in the search tree?
",3.3.a repeated state is a state that is reached by a loopy path.,5183
25,1952,chapter3_1,midterm_1,T5,GoodSummary,What define a search problem?,"State space, initial state, set of possible actions, transition model action cost function, and goal states",1952
26,1605,chapter16_2,midterm_2,GPT3,Fewshot,"What is orderability?
",Orderability is the requirement that preferences be transitive.,1605
27,2733,chapter2_2,midterm_1,T5,BadSummary,What is AI usually concerned with?,consequentialism,2733
28,2822,chapter5_1,midterm_1,T5,BadSummary,Game can be defined as a search problem using what?,"initial state, players, actions, result(s, a), terminal test(s), utility(s, p)",2822
29,1328,slp_chapter4_9,midterm_2,GPT3,Zero,"What is a test set?
",A test set is the set of documents that are not used to build the model but are used to test the model.,1328
30,459,chapter7_1,midterm_1,GPT3,GoodSummary,"What is an agent's kb?
",An agent's kb is a set of sentences which are represented in knowledge representation language.,459
31,770,chapter5_2,midterm_1,GPT3,BadSummary,"What is the pseudocode of the minmax algorithm?
",The pseudocode of the minmax algorithm is,770
32,1514,chapter5_2,midterm_1,GPT3,Fewshot,"What is the memory requirement of the minmax algorithm?
","The memory requirement of the minmax algorithm is o(bd), where b is the number of legal moves and d is the depth of the game tree.",1514
33,659,slp_chapter5_4,midterm_2,GPT3,GoodSummary,"What is the difference between stochastic gradient descent and mini-batch training?
","Stochastic gradient descent is an online function, which minimizes the loss function by computing the gradient after each training example then nudging theta in",659
34,6426,chapter_3_4_1,1st midterm,T5,From GPT-3 generated summary,Breadth-first search always finds a solution with what?,a minimal number of actions,6426
35,1434,slp_chapter6_11,midterm_2,GPT3,Zero,"What is the process of reducing bias in embeddings called?
",The process of reducing bias in embeddings is called debiasing.,1434
36,1609,chapter16_2,midterm_2,GPT3,Fewshot,"What is monotonicity?
",Monotonicity is the requirement that preferences be monotonic.,1609
37,6309,chapter_2_2_3,1st midterm,T5,From GPT-3 generated summary,The rational choice depends only on what?,percept sequence to date,6309
38,744,chapter3_1,midterm_1,GPT3,BadSummary,"What is an action cost function?

",An action cost function is a function that refects the performance measures of the problem solving agent.,744
39,226,slp_chapter4_7,midterm_2,GPT3,Best Condition - with Davinci,"What is a confusion matrix for visualizing how an algorithm performs with respect to human gold labels?
",A confusion matrix is a way of visualizing how an algorithm performs with respect to human gold labels.,226
40,2808,chapter3_2,midterm_1,T5,BadSummary,What is the answer to the np-hard Criterion Breadth- Uniform- Depth-lim Iterative-deep Bidirectional,Yes,2808
41,1266,chapter19_1,midterm_2,GPT3,Zero,"What is transfer learning?
",Transfer learning is when knowledge from one domain is transferred to another.,1266
42,2997,chapter19_6,midterm_2,T5,BadSummary,What do we want to make smaller so that hw(x) outputs a 0. - If y is 0 but h,w*x,2997
43,936,slp_chapter4_8,midterm_2,GPT3,BadSummary,"What is the difference between lstm and rnn?
","The main difference between lstm and rnn is that lstm uses a local state, whereas rnn uses a global state.",936
44,3038,slp_chapter5_6,midterm_2,T5,BadSummary,How many classes does multinomial logistic regression have?,more than 2 classes,3038
45,852,chapter12_4,midterm_2,GPT3,BadSummary,"What is canonical decomposition?
",Canonical decomposition is a method of representing the problem as a set of independent problems and then solving each problem separately.,852
46,2989,chapter19_5,midterm_2,T5,BadSummary,What theory is most likely to be wrong after only a few examples?,Computational learning theory,2989
47,2047,chapter6_1,midterm_1,T5,GoodSummary,What is the name of the set of variables in a CSP?,X,2047
48,3650,slp_chapter7_5,midterm_2,T5,Zero,Why are neural language models less interpretable than n-gram models?,more complex and slow to train,3650
49,428,chapter16_2,midterm_1,GPT3,GoodSummary,"What is orderability?
",Orderability is the constraint that states that a decision maker must prefer a lottery or rate them equal.,428
50,978,slp_chapter9_3,midterm_2,GPT3,BadSummary,"How do you randomly sample other words in the lexicon to get negative samples?
",Randomly sample other words in the lexicon to get negative samples.,978
51,4743,SLP_chapter3_5,midterm_2,T5,Best Condition - with Davinci,What are some methods of smoothing?,"Laplace smoothing, add-k smoothing, and Kneser-Ney smoothing",4743
52,4923,slp_chapter5_5,midterm_2,T5,Best Condition - with Davinci,What is the L2 norm the same as?,Euclidean distance,4923
53,1137,chapter7_4,midterm_1,GPT3,Zero,"What is propositional logic?
",Propositional logic is a formal system that defines the allowable atomic sentences that can be used to construct complex sentences.,1137
54,5140,chapter_2_4_3,1st midterm,GPT3,From raw text,"What is the difference between the effects of the agent’s actions and how the world evolves independently of the agent?
","The difference between the effects of the agent’s actions and how the world evolves independently of the agent is that the effects of the agent’s actions are how the world changes over time, and how the world evolves independently of the agent is how the world evolves without the agent taking any actions.",5140
55,6244,chapter_27_1_3,1st midterm,T5,From GPT-3 generated summary,The text criticizes the claim that machines are inferior to humans because they are limited by what?,incompleteness theorem,6244
56,6216,chapter_1_1_3,1st midterm,T5,From GPT-3 generated summary,Who was one of the first people to try and create patterns for irrefutable reasoning processes?,Aristotle,6216
57,4912,slp_chapter5_3,midterm_2,T5,Best Condition - with Davinci,What is the negative log likelihood loss generally called?,cross-entropy loss,4912
58,4273,slp_chapter9_1,midterm_2,T5,Fewshot,Neural Language models can handle what?,longer histories,4273
59,340,slp_chapter6_11,midterm_2,GPT3,Best Condition - with Davinci,"What is allocational harm?
",Allocational harm is a system that unfairly allocates resources (jobs or credit) to different groups.,340
60,6388,chapter_3_1_2,1st midterm,T5,From GPT-3 generated summary,What does the author say a good problem formulation has?,the right level of detail,6388
61,324,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,324
62,5782,chapter_3,1st midterm,T5,From raw text,"When the correct action to take is not immediately obvious, an agent may need to do what?",plan ahead,5782
63,5206,chapter_3_3_4,1st midterm,GPT3,From raw text,"1
",To,5206
64,2316,chapter12_7,midterm_2,T5,GoodSummary,What is a good example of how to use to improve choosing a square in the Wumpus world?,theorems,2316
65,4035,chapter12_2,midterm_2,T5,Fewshot,What is a function mapping the domain of possible worlds?? to some range?,Random variable,4035
66,4115,chapter13_3,midterm_2,T5,Fewshot,Why is inference in Bayes nets hard?,NP-hard,4115
67,6118,chapter_2_4_3,1st midterm,GPT3,From GPT-3 generated summary,"What is a transition model?
",A transition model is a model of how the world will change over time.,6118
68,4149,chapter19_3,midterm_2,T5,Fewshot,What is another method to combat overfitting?,Early stopping,4149
69,3193,chapter3_3,midterm_1,T5,Zero,What are search algorithms used for?,to find solutions to problems or to indicate failure if no solution exists,3193
70,1776,slp_chapter4_7,midterm_2,GPT3,Fewshot,"What is the f-measure?
",The f-measure incorporates both aspects of precision and recall.,1776
71,742,chapter3_1,midterm_1,GPT3,BadSummary,"What is a solution sequence?

",A solution sequence is a sequence of actions that reaches a goal.,742
72,3024,slp_chapter5_1,midterm_2,T5,BadSummary,What is sigmod?,objective function for learning,3024
73,1258,chapter13_2,midterm_2,GPT3,Zero,"What is compactness of bayesian networks?
",Compactness of bayesian networks is an example of a general property of locally structured (sparse) systems.,1258
74,2634,slp_chapter7_5,midterm_2,T5,GoodSummary,Feedforward Neural Language Modeling is compared to what other model?,n-gram models,2634
75,5174,chapter_3_3_1,1st midterm,GPT3,From raw text,"What is the general approach called?
",The general approach is called best-first search.,5174
76,6163,chapter_3_3_2,1st midterm,GPT3,From GPT-3 generated summary,"What determines what an optimal solution is?
",What constitutes an optimal solution depends on the objective function being minimized.,6163
77,6070,chapter_2,1st midterm,GPT3,From GPT-3 generated summary,"What is the diversity of environments?
",The diversity of environments is the variety of different situations that an agent can encounter.,6070
78,834,chapter22_4,midterm_2,GPT3,BadSummary,"What is an evaluation function?
",An evaluation function is a compact measure of desirability for potentially vast state spaces.,834
79,4514,chapter6_2,midterm_1,T5,Best Condition - with Davinci,What does AC-3 maintain a queue of to consider?,arcs,4514
80,584,chapter19_2,midterm_2,GPT3,GoodSummary,"What is the difference between a model and a hypothesis?
",A model is a hypothesis.,584
81,5682,chapter_2_4_2,1st midterm,T5,From raw text,What do simple reflex agents select actions on?,current percept,5682
82,5316,chapter_1_1_4,1st midterm,T5,From raw text,What is not feasible in complex environments?,perfect rationality,5316
83,1840,slp_chapter7_7,midterm_2,GPT3,Fewshot,"
",3.,1840
84,441,chapter6_2,midterm_1,GPT3,GoodSummary,"What is constraint propagation?
",Constraint propagation is the process of changing the values of some variables based on the values of others.,441
85,460,chapter7_1,midterm_1,GPT3,GoodSummary,"What are non-derived sentences?
",Non-derived sentences are axioms.,460
86,1772,slp_chapter4_7,midterm_2,GPT3,Fewshot,"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 using system output and gold labels.,1772
87,1463,chapter2_2,midterm_1,GPT3,Fewshot,"What is the importance of rationality in ai?
",Rationality is important in ai because it helps ensure that agents do the right thing.,1463
88,2942,SLP_chapter3_1,midterm_2,T5,BadSummary,"For bigram, how many n-gram probabilities does $P(w_n|w_?? )=?? frac",n-1,2942
89,5537,chapter_2_2_2,1st midterm,T5,From raw text,What defines the criterion of success?,The performance measure,5537
90,109,chapter12_3,midterm_2,GPT3,Best Condition - with Davinci,"What is the probabilistic inference procedure for a single variable x and list of evidence variables e?
","The probabilistic inference procedure for a single variable x and list of evidence variables e is to query the probability p(x|e) can be evaluated as: p(x|e) = αp(x,e) = α ∑_y p(x,e,y).",109
91,5340,chapter_1_1_5,1st midterm,T5,From raw text,What is the sole objective for a machine?,winning,5340
92,4649,chapter22_4,midterm_2,T5,Best Condition - with Davinci,What can the utility function be approximated with?,weighted linear combinations of features,4649
93,5088,chapter_27_1_4,1st midterm,GPT3,From raw text,"What is the purpose of the turing test?
",The purpose of the turing test is to measure a program’s ability to fool an interrogator into thinking the program is human.,5088
94,3302,chapter6_3,midterm_1,T5,Zero,What chooses the next value to examine based on the value that rules out the fewest choices for the neighboring variables in the constraint graph?,The least-constraining-value heuristic,3302
95,6024,chapter_1_1_3,1st midterm,GPT3,From GPT-3 generated summary,"What does this mean?
",This means that it allows for a comprehensive model of rational thought that can be used to make predictions about the future.,6024
96,1098,chapter6_2,midterm_1,GPT3,Zero,"What does ac-3 do to make a csp problem arc-consistent?
","Ac-3 maintains a queue of arcs to consider, and initially, all arcs are in the queue. then, it pops out an arbitrary arc (x_i, x_j) and makes the variable x_i arc-consistent with x_j.",1098
97,4992,slp_chapter9_2,midterm_2,T5,Best Condition - with Davinci,What type of vectors are low-dimensional?,dense vectors,4992
98,5043,chapter_1_1,1st midterm,GPT3,From raw text,"What is the behavioralist approach to ai?
",The behavioralist approach to ai is an approach,5043
99,4443,chapter3_4,midterm_1,T5,Best Condition - with Davinci,What is the following?,comparison between different search algos,4443
100,3928,chapter6_5,midterm_1,T5,Fewshot,What is the domain of a tree decomposition?,tuples of variables,3928
101,999,slp_chapter6_11,midterm_2,GPT3,BadSummary,"What are embeddings?
",Embeddings are systems that reflect the statistics of their input and amplify bias.,999
102,3357,chapter22_1,midterm_2,T5,Zero,What is an alternative to supervised learning from previous chapters?,Reinforcement learning,3357
103,3469,chapter13_2,midterm_2,T5,Zero,What is a Bayes net?,a directed acyclic graph,3469
104,5398,chapter_27_1_3,1st midterm,T5,From raw text,Who did the mathematical objection Turing (1936) and Gödel (1931) prove that mathematical questions are unanswerable by particular formal systems?,Lucas,5398
105,1717,chapter19_1,midterm_2,GPT3,Fewshot,"What are the components of an agent?
","The components of an agent include a direct mapping from conditions on the current state to an action, means to infer relevant properties of the world, and information about the way the world evolves and the results of actions an agent takes.",1717
106,6034,chapter_27_1,1st midterm,GPT3,From GPT-3 generated summary,"What is human-level ai/general ai?
","Human-level ai/general ai is a program that can solve an arbitrarily wide variety of tasks, including novel ones, and do so as well as a human.",6034
107,4966,slp_chapter7_3,midterm_2,T5,Best Condition - with Davinci,What forms a representation of the output of the hidden layer?,vector,4966
108,2554,slp_chapter5_1,midterm_2,T5,GoodSummary,What helps binary logistic regression make a decision about class of a new input observation?,Sigmoid classifier,2554
109,6211,chapter_1_1_1,1st midterm,T5,From GPT-3 generated summary,Why have researchers devoted little effort to passing the Turing test?,study the underlying principles of intelligence,6211
110,6382,chapter_3_1,1st midterm,T5,From GPT-3 generated summary,What type of strategy recommends different future actions depending on what percepts arrive?,branching strategy,6382
111,3315,chapter7_2,midterm_1,T5,Zero,What is the environment of the Wumpus world?,"deterministic, discrete, static, and single-agent",3315
112,1495,chapter3_4,midterm_1,GPT3,Fewshot,"What is the difference between bfs and dfs?
",Bfs is a search algorithm that uses late goal testing. dfs is a search algorithm that uses early goal testing.,1495
113,427,chapter16_2,midterm_1,GPT3,GoodSummary,"What are the six constraints to obey?
","The six constraints to obey are orderability, transitivity, continuity, substitutability, monotonicity, and decomposability.",427
114,415,chapter5_3,midterm_1,GPT3,GoodSummary,"What is the expected utility of a terminal state?
",The expected utility of a terminal state is the utility of the state from the current player's perspective.,415
115,5085,chapter_27_1_3,1st midterm,GPT3,From raw text,"What is the problem with lucas's claim?
",The problem with lucas's claim is that an agent should not be ashamed that it cannot establish the truth of some sentence while other agents can.,5085
116,4201,slp_chapter4_10,midterm_2,T5,Fewshot,What are harms caused by a system that demeans a social group called?,Representational harms,4201
117,5659,chapter_2_4,1st midterm,T5,From raw text,What do we now have to talk about?,how the insides work,5659
118,6415,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
119,6028,chapter_1_1_5,1st midterm,GPT3,From GPT-3 generated summary,,"The text argues that a better model would be one in which the machine is uncertain about the human's objectives, and therefore acts cautiously.
",6028
120,5145,chapter_2_4_6,1st midterm,GPT3,From raw text,"How many components are there in a learning agent?
","There are four components in a learning agent: the learning element, the performance element, the critic, and the problem generator.",5145
121,190,chapter19_5,midterm_2,GPT3,Best Condition - with Davinci,"What is computational learning theory?
",Computational learning theory is a body of knowledge that deals with how to build machines that can learn.,190
122,3121,slp_chapter6_12,midterm_2,T5,BadSummary,What causes embedding algorithms to produce different results even from the same dataset?,randomness in the initialization and the random negative sampling,3121
123,884,chapter19_3,midterm_2,GPT3,BadSummary,"1.what is a decision tree representation of a function that maps vector of attributes values to single output value?
",1.a decision tree is a representation of a function that maps vector of attributes values to a single output value.,884
124,6321,chapter_2_2_3,1st midterm,T5,From GPT-3 generated summary,What does the agent act when the environment is completely known a priori and completely predictable?,correct,6321
125,6137,chapter_3,1st midterm,GPT3,From GPT-3 generated summary,"What is the simplest search algorithm?
",The simplest search algorithm is the episodic search algorithm.,6137
126,237,slp_chapter4_9,midterm_2,GPT3,Best Condition - with Davinci,"Is a result statistically significant if the p-value is small?
",Yes.,237
127,2597,slp_chapter5_4,midterm_2,T5,GoodSummary,Stochastic gradient descent can also use what?,batch training or mini-batch training,2597
128,5376,chapter_27_1_1,1st midterm,T5,From raw text,"Under what approach do robotics, vision, and other sensors become central, not peripheral?",embodied cognition,5376
129,4803,chapter19_3,midterm_2,T5,Best Condition - with Davinci,Decision trees can be what with interpretable results?,intuitive,4803
130,6410,chapter_3_3_3,1st midterm,T5,From GPT-3 generated summary,How can we remember all previously reached states?,best-first search,6410
131,4650,chapter22_4,midterm_2,T5,Best Condition - with Davinci,The approximate utility function can be combined with what for more accurate decisions?,look-ahead search,4650
132,5204,chapter_3_3_4,1st midterm,GPT3,From raw text,"1
",To,5204
133,943,slp_chapter5_1,midterm_2,GPT3,BadSummary,"What is a discriminative model?
",A discriminative model is a model that discriminates between different data.,943
134,254,slp_chapter5_3,midterm_2,GPT3,Best Condition - with Davinci,"What is the resulting loss function?
","The resulting loss function is the negative log likelihood loss, generally called the cross-entropy loss.",254
135,1724,chapter19_2,midterm_2,GPT3,Fewshot,"What is a hypothesis?
","A hypothesis is a model drawn from a model class, or a function from a function class.",1724
136,3815,chapter3_3,midterm_1,T5,Fewshot,What is a special case of a redundant path?,A cycle,3815
137,5215,chapter_3_4,1st midterm,GPT3,From raw text,,"An uninformed search algorithm is given no clue about how close a state is to the goal(s).
",5215
138,57,chapter16_1,midterm_2,GPT3,Best Condition - with Davinci,"What is the name for decision making with uncertain outcomes?
",Decision making with uncertain outcomes is also called decision making with unknown outcomes.,57
139,2368,chapter13_2,midterm_2,T5,GoodSummary,What is an example of Bayesian nets?,general property locally structured (sparse) systems,2368
