,Unnamed: 0,Chapter,Midterm,Model,Condition,Question,Answer,questionId
0,600,chapter19_5,midterm_2,GPT3,GoodSummary,"What is the difference between a hypothesis that is consistent with a large set of training examples and a hypothesis that is probably approximately correct?
","The difference between a hypothesis that is consistent with a large set of training examples and a hypothesis that is probably approximately correct is that the former is a hypothesis that is wrong, while the latter is a hypothesis that is right.",600
1,1368,slp_chapter7_2,midterm_2,GPT3,Zero,"How many layers does a network of perceptrons need in order to solve the xor problem?
",A network of perceptrons needs at least two layers in order to solve the xor problem.,1368
2,2806,chapter3_2,midterm_1,T5,BadSummary,8-puzzle belongs to the family of what?,sliding-block puzzles,2806
3,1175,chapter17_3,midterm_2,GPT3,Zero,"What is the optimal policy maximized?
",The optimal,1175
4,1383,slp_chapter7_6,midterm_2,GPT3,Zero,"What is a loss function?
",A loss function is a function that measures the distance between the system output and the gold output.,1383
5,606,chapter19_6,midterm_2,GPT3,GoodSummary,"What is multivariable linear regression?
",Multivariable linear regression is fitting with a straight line.,606
6,6361,chapter_2_4_6,1st midterm,T5,From GPT-3 generated summary,What is the last component of the learning agent?,problem generator,6361
7,2685,slp_chapter6_8,midterm_2,T5,GoodSummary,What is the popular family of BERT representations?,dynamic contextual embeddings,2685
8,4868,slp_chapter4_5,midterm_2,T5,Best Condition - with Davinci,What are true positives?,finding what we are supposed to be looking for,4868
9,5008,slp_chapter6_4,midterm_2,T5,Best Condition - with Davinci,What is the dot product of two vectors?,the sum of the products of the elements of each vector times the other vector,5008
10,1392,slp_chapter9_1,midterm_2,GPT3,Zero,"What are the advantages of recurrent neural language models over feed-forward neural language models?
","Recurrent neural language models have several advantages over feed-forward neural language models, including the ability to handle longer histories, generalize over contexts of similar words, and achieve higher predictive accuracy.",1392
11,4242,slp_chapter7_1,midterm_2,T5,Fewshot,What is a standard non-linearity that maps values from -?? to +?? to values between 0 and 1?,sigmoid function,4242
12,5843,chapter_3_1_2,1st midterm,T5,From raw text,What device would we use to drive between Sibiu and Rimnicu Vilcea?,the radio,5843
13,2111,chapter7_2,midterm_1,T5,GoodSummary,What do Wumpus agents draw conclusions from?,available info,2111
14,5493,chapter_2_1,1st midterm,T5,From raw text,"By specifying the agent’s choice of action for every possible percept sequence, we have said what about the agent?",more or less everything,5493
15,5520,chapter_2_2,1st midterm,T5,From raw text,What does a rational agent do with a vacuum-cleaner?,what you ask for is what you get,5520
16,3318,chapter7_3,midterm_1,T5,Zero,What is the set of all models of a?,M(a),3318
17,775,chapter16_1,midterm_1,GPT3,BadSummary,"What is the definition of an agent's preferences captured by a utility function?
",An agent's preferences captured by a utility function is a mapping from each state to a number that captures its desirability.,775
18,4979,slp_chapter7_6,midterm_2,T5,Best Condition - with Davinci,What is an optimization algorithm used to find parameters that minimize the loss function?,gradient descent,4979
19,3616,slp_chapter5_5,midterm_2,T5,Zero,What is the L2 norm the same as?,Euclidean distance,3616
20,4381,chapter2_2,midterm_1,T5,Best Condition - with Davinci,What is gathering?,Information,4381
21,5585,chapter_2_3,1st midterm,T5,From raw text,What are we almost ready to build now that we have a definition of rationality?,rational agents,5585
22,4274,slp_chapter9_1,midterm_2,T5,Fewshot,What can neural language models do?,generalize over contexts of similar words,4274
23,1850,slp_chapter9_3,midterm_2,GPT3,Fewshot,"What do you need to use logistic regression to train a classifier to distinguish those two cases?
","In order to use logistic regression to train a classifier to distinguish those two cases, you need a function that maps a set of inputs to a set of outputs where the outputs represent the probability of a positive example.",1850
24,3509,chapter19_3,midterm_2,T5,Zero,What does entropy measure?,uncertainty of a random variable,3509
25,3138,chapter27_1,midterm_1,T5,Zero,The embodied cognition approach stated that it makes no sense to consider what separately?,brain,3138
26,1074,chapter5_3,midterm_1,GPT3,Zero,"What is the effect of alpha beta?
",The effect of alpha beta is depending on the order in which states are examined.,1074
27,1358,slp_chapter5_6,midterm_2,GPT3,Zero,"What are the features in a multinomial logistic regression?
",The features in a multinomial logistic regression are the same as in a regular logistic regression.,1358
28,60,chapter16_2,midterm_2,GPT3,Best Condition - with Davinci,"What is orderability?
",Orderability is the constraint on rational preferences that requires that preferences be transitive.,60
29,5662,chapter_2_4,1st midterm,T5,From raw text,What must the architecture have if the program is going to recommend actions like Walk?,legs,5662
30,6216,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
31,5154,chapter_3_1,1st midterm,GPT3,From raw text,"What is a problem?
",A problem is a,5154
32,103,chapter12_2,midterm_2,GPT3,Best Condition - with Davinci,"What is a probability space?
",A probability space is a set of all possible worlds which are mutually exclusive and exhaustive.,103
33,3655,slp_chapter7_5,midterm_2,T5,Zero,What is a vector that has one element equal to 1?,one-hot vector,3655
34,416,chapter5_5,midterm_1,GPT3,GoodSummary,"What is a stochastic game?
",A stochastic game is a game where the outcome is not deterministic and depends on chance.,416
35,6354,chapter_2_4_6,1st midterm,T5,From GPT-3 generated summary,Which element is responsible for selecting external actions?,performance element,6354
36,3001,slp_chapter4_1,midterm_2,T5,BadSummary,What is the definition of a conditional probability?,P(x|y) = P(y|x)P(x)/ P(y),3001
37,4566,chapter7_5,midterm_1,T5,Best Condition - with Davinci,Valid sentences are also known as what?,tautologies,4566
38,1416,slp_chapter6_4,midterm_2,GPT3,Zero,"What is the dot product of the two vectors 
",The dot product of the two vectors is,1416
39,3928,chapter6_5,midterm_1,T5,Fewshot,What is the domain of a tree decomposition?,tuples of variables,3928
40,3500,chapter19_2,midterm_2,T5,Zero,What occurs when the data pays too much attention to particular data sets and performs poorly on unseen data?,Overfitting,3500
41,1509,chapter5_1,midterm_1,GPT3,Fewshot,"What is a utility function? 
",A utility function is a function that assigns a value to a particular state.,1509
42,989,slp_chapter6_2,midterm_2,GPT3,BadSummary,"That can be asked about a word?
",The most abstract,989
43,2756,chapter2_3,midterm_1,T5,BadSummary,Discrete refers to a number that is what?,finite,2756
44,5565,chapter_2_2_3,1st midterm,T5,From raw text,How does the agent act when the environment is completely known a priori and completely predictable?,correct,5565
45,2704,slp_chapter6_10,midterm_2,T5,GoodSummary,"What does distance(x,a* - a + b) mean?",argmin,2704
46,4990,slp_chapter9_2,midterm_2,T5,Best Condition - with Davinci,What can be expressed in terms of a word sequence in terms of the word vectors for the words in that sequence?,The joint probability function,4990
47,1752,slp_chapter4_2,midterm_2,GPT3,Fewshot,"What is a parametric model?
",A parametric model is a model that has a fixed size on the number of parameters.,1752
48,2401,chapter13_3,midterm_2,T5,GoodSummary,Bayes net #P-hard is harder than what?,NP-complete,2401
49,6391,chapter_3_3,1st midterm,T5,From GPT-3 generated summary,What is a tree that shows the possible paths that could be taken to reach a goal state?,a search tree,6391
50,5219,chapter_3_4_1,1st midterm,GPT3,From raw text,"What is an exponential-complexity search problem?
",An exponential-complexity search problem is a search problem with a time or space complexity that is exponential in the size of the search space.,5219
51,5123,chapter_2_3_2,1st midterm,GPT3,From raw text,"What are the dimensions along which task environments can be categorized?
","The range of task environments that might arise in ai is obviously vast. we can, however, identify a fairly small number of dimensions along which task environments can be categorized. these dimensions determine, to a large extent, the appropriate agent design and the applicability of each of the principal families of techniques for agent implementation.",5123
52,1470,chapter2_3,midterm_1,GPT3,Fewshot,"What is a task environment property?
",A task environment property is a property of the environment in which the agent is working.,1470
53,3116,slp_chapter6_12,midterm_2,T5,BadSummary,What is a common set of ratings from 0 to 10 for 353 noun pairs?,WordSim-353,3116
54,3890,chapter16_3,midterm_1,T5,Fewshot,Normalized utilities use a scale of what to 1?,0,3890
55,4311,slp_chapter6_10,midterm_2,T5,Fewshot,The word2vec skip-gram model is trained on positive training instances that have a window of what?,+/- 2,4311
56,5034,chapter_1,1st midterm,GPT3,From raw text,"What is artificial intelligence?
",Artificial intelligence is the study of how to build intelligent entities—machines that can compute how to act effectively and safely in a wide variety of novel situations.,5034
57,463,chapter7_1,midterm_1,GPT3,GoodSummary,"How is an agent program called?
","An agent program is called by telling its kb what it perceives, then asking its kb what to do (action), and finally telling its kb what it chose to do.",463
58,6021,chapter_1_1_3,1st midterm,GPT3,From GPT-3 generated summary,"What was developed in the 19th century?
","In the 19th century, logicians developed a precise notation for statements about objects in the world and the relations among them.",6021
59,5587,chapter_2_3,1st midterm,T5,From raw text,What do task environments come in?,a variety of flavors,5587
60,6128,chapter_2_4_5,1st midterm,GPT3,From GPT-3 generated summary,"What is a disadvantage of a goal-based agent?
",A goal-based agent is less flexible and cannot learn.,6128
61,436,chapter16_3,midterm_1,GPT3,GoodSummary,"What is descriptive theory?
",Descriptive theory is a description of how actual agents act.,436
62,6448,chapter_3_4_4,1st midterm,T5,From GPT-3 generated summary,What sets a limit on how deep the search can go?,depth-limited search,6448
63,1411,slp_chapter6_3,midterm_2,GPT3,Zero,"What does the cell in the matrix represent?
",The cell in the matrix represents how often a word occurs in a document.,1411
64,2973,chapter13_1,midterm_2,T5,BadSummary,What connects pairs of nodes?,Directed links or arrows,2973
65,1381,slp_chapter7_5,midterm_2,GPT3,Zero,"What is forward inference, or decoding?
","Forward inference, or decoding, is the task of running a forward pass on the network to produce a probability distribution over possible outputs, in this case next words.",1381
66,5,chapter16_3,midterm_1,GPT3,Best Condition - with Davinci,"What is a micromort?

",A micromort is one in a million chance of death.,5
67,2669,slp_chapter6_2,midterm_2,T5,GoodSummary,What is the idea of representing a word as a point in a multidimensional semantic space that is derived from the distributions of word neighbors,vector semantics,2669
68,926,slp_chapter4_7,midterm_2,GPT3,BadSummary,"* can use confusion matrix to plot roc curve 
* roc curve shows the relationship between precision and recall
questions to ","
what are gold labels? 
how can we build a confusion matrix for a visualizing how an algorithm performs with respect to gold labels? 
what is accuracy? 
what is precision? 
what is recall? 
what is f-me",926
69,2338,SLP_chapter3_4,midterm_2,T5,GoodSummary,What is a sentence that never occurs in the training set but does in the test set called?,zero,2338
70,5989,chapter_3_4_4,1st midterm,T5,From raw text,How does breadth-first do this?,by storing all nodes in memory,5989
71,6165,chapter_3_3_3,1st midterm,GPT3,From GPT-3 generated summary,"What is a cycle?
","A cycle is a path from one state to another state, and then back to the first state.",6165
72,2631,slp_chapter7_4,midterm_2,T5,GoodSummary,What are words represented as?,word2vec or GloVe embeddings,2631
73,5232,chapter_3_4_6,1st midterm,GPT3,From raw text,"What is the difference between depth-first search and iterative deepening with stack?
",Depth-first search explores the current node before exploring any other nodes. iterative deepening with stack explores the current node and all of its children before exploring any other nodes.,5232
74,911,slp_chapter4_3,midterm_2,GPT3,BadSummary,"What is the difference between the two algorithms?
","The difference between the two algorithms is that the duplicate word
removal algorithm removes duplicate words before concatenating the docs into a
single document",911
75,4183,slp_chapter4_7,midterm_2,T5,Fewshot,How can we build a confusion matrix for visualizing how an algorithm performs with respect to human gold labels?,system output and gold labels,4183
76,36,chapter7_2,midterm_1,GPT3,Best Condition - with Davinci,"What is the environment of the wumpus world?
","The environment of the wumpus world is deterministic, discrete, static, and single agent.",36
77,3682,slp_chapter6_1,midterm_2,T5,Zero,What is when two words are related to each other in some way but their meanings are not necessarily similar?,Word relatedness,3682
78,4806,chapter19_3,midterm_2,T5,Best Condition - with Davinci,The importance of a decision tree is measured by what?,entropy,4806
79,799,chapter6_5,midterm_1,GPT3,BadSummary,"What is cutset conditioning?
",Cutset conditioning is the process of removing and assigning s (a cycle cutset) such that the,799
80,1854,slp_chapter6_1,midterm_2,GPT3,Fewshot,"What is word relatedness?
","Word relatedness is when two words are related to each other in some way, but their meanings are not necessarily similar.",1854
81,1931,chapter2_2,midterm_1,T5,GoodSummary,Rational agents can learn from what?,their environment,1931
82,1882,slp_chapter6_11,midterm_2,GPT3,Fewshot,"What is debias?
",Debias is the process of reducing bias in embeddings.,1882
83,2898,chapter16_2,midterm_2,T5,BadSummary,What is the utility of a lottery?,the sum of the probability of each outcome times the utility of that outcome,2898
84,3749,chapter2_1,midterm_1,T5,Fewshot,"What does the vacuum cleaner have that allow it to move left, right, and pick up dirt?",actuators,3749
85,3002,slp_chapter4_2,midterm_2,T5,BadSummary,What do parametric models have on number of parameters?,fixed size,3002
86,5063,chapter_27,1st midterm,GPT3,From raw text,"What is ai?
",Ai is the study of how to make machines that act intelligently.,5063
87,4522,chapter6_3,midterm_1,T5,Best Condition - with Davinci,"When a variable has no legal values left to assign, what is the term for ing search?",backtrack,4522
88,2747,chapter2_3,midterm_1,T5,BadSummary,What will not depend on the previous episode?,The next episode,2747
89,830,chapter22_1,midterm_2,GPT3,BadSummary,"What is the advantage of a little bit of experience in reinforcement learning?

","A little bit of experience is helpful for reinforcement learning, especially in simulated environments.",830
90,6067,chapter_27_2_2,1st midterm,GPT3,From GPT-3 generated summary,"What experiments have helped to resolve some of the issues of the problem of consciousness?
",Experiments conducted by neuroscientists and philosophers,6067
91,3490,chapter19_1,midterm_2,T5,Zero,What is when an agent is observed input-output pairs and learns a function that maps from input to output?,Supervised learning,3490
92,6403,chapter_3_3_3,1st midterm,T5,From GPT-3 generated summary,What is a path that is just a worse way to get to the same state?,A redundant path,6403
93,1794,slp_chapter5_2,midterm_2,GPT3,Fewshot,"What is a loss function?
",A loss function is a measure of how close the current label (yˆ) is to the true gold label y.,1794
94,3117,slp_chapter6_12,midterm_2,T5,BadSummary,What is a common set of ratings from 0 to 10 for 353 noun pairs?,WordSim-353,3117
95,4100,chapter13_1,midterm_2,T5,Fewshot,What does each node correspond to?,random variable,4100
96,1866,slp_chapter6_4,midterm_2,GPT3,Fewshot,"What is the dot product of the vector with itself?
",The dot product of the vector with itself is,1866
97,3106,slp_chapter6_10,midterm_2,T5,BadSummary,What does the quick brown fox jump over?,lazy dog,3106
98,232,slp_chapter4_8,midterm_2,GPT3,Best Condition - with Davinci,"What are the two important concepts that help us understand how a neural network learns?

",The two important concepts that help us understand how a neural network learns are the gradient of the function and the performance of the function.,232
99,5224,chapter_3_4_3,1st midterm,GPT3,From raw text,"How is depth-first search implemented?
",Depth-first search is implemented as a call to best-,5224
100,796,chapter6_4,midterm_1,GPT3,BadSummary,"What is the max conflict search algorithm?
",The max conflict search algorithm selects the value that results in the maximum number of conflicts with other variables.,796
101,6232,chapter_27,1st midterm,T5,From GPT-3 generated summary,The text touches on what aspect of AI?,safety,6232
102,6169,chapter_3_3_3,1st midterm,GPT3,From GPT-3 generated summary,"What is a cycle in a search tree?
","A cycle is a path from one state to another state, and then back to the first state.",6169
103,3506,chapter19_3,midterm_2,T5,Zero,Decision trees can generate error or noise in the data if the results are what?,nondeterministic,3506
104,6184,chapter_3_4_2,1st midterm,GPT3,From GPT-3 generated summary,"What is dijkstra's algorithm called?
",Dijkstra's algorithm is called uniform-cost search because it expands nodes in order of their path cost.,6184
105,5788,chapter_3,1st midterm,T5,From raw text,What is the term for an agent that can estimate how far it is from the goal?,uninformed algorithms,5788
106,331,slp_chapter6_8,midterm_2,GPT3,Best Condition - with Davinci,"What is word2vec?
",Word2vec is a learning method that learns the probability of a word occurring near another word.,331
107,4751,SLP_chapter3_7,midterm_2,T5,Best Condition - with Davinci,What can be built from the web?,Large language models,4751
108,1959,chapter3_2,midterm_1,T5,GoodSummary,What is another common problem?,Route finding,1959
109,3838,chapter3_5,midterm_1,T5,Fewshot,What does an admissible h(n) function do?,never underestimates the cost of reaching the goal,3838
110,473,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
111,6151,chapter_3_3,1st midterm,GPT3,From GPT-3 generated summary,"What is the difference between the state space and the search tree?
","The state space is the set of all possible states that a problem could be in, and the search tree is the set of all possible paths that could be taken to reach a goal state.",6151
112,839,chapter22_4,midterm_2,GPT3,BadSummary,"What is deep reinforcement learning?
",Deep reinforcement learning is a method for constructing a more accurate decision.,839
113,5747,chapter_2_4_6,1st midterm,T5,From raw text,Who tells the learning element how well the agent is doing with respect to a fixed performance standard?,The critic,5747
114,255,slp_chapter5_4,midterm_2,GPT3,Best Condition - with Davinci,"What are the two requirements for a function to be convex?
",A function is convex if it has just one minimum and no local minima to get stuck in.,255
115,507,chapter22_3,midterm_2,GPT3,GoodSummary,"What is the difference between q-learning and sarsa?
","Q-learning backs up the q-value from the best action in s', while sarsa waits until action is taken and backs up the q-value for that action.",507
116,1680,SLP_chapter3_2,midterm_2,GPT3,Fewshot,"What is the inverse probability of the test set?
",The inverse probability of the test set is the probability of the test set given the language model.,1680
117,28,chapter6_5,midterm_1,GPT3,Best Condition - with Davinci,"What is the tree decomp approach?
","The tree decomp approach is an alternative to cutset conditioning that takes o(nd^{w+1}) time.

question",28
118,4973,slp_chapter7_5,midterm_2,T5,Best Condition - with Davinci,What does a feedforward neural language model consist of?,"input layer, a hidden layer, and an output layer",4973
119,1371,slp_chapter7_3,midterm_2,GPT3,Zero,"What is a feedforward network?
","A feedforward network is a type of neural network in which the units are connected with no cycles, and the outputs from units in each layer are passed to units in the next higher layer.",1371
120,6133,chapter_2_4_6,1st midterm,GPT3,From GPT-3 generated summary,"What is the most general case of learning directly from the percept sequence?
","The most general case of learning directly from the percept sequence involves learning ""what my actions do"" and ""how the world evolves"" in response to its actions.",6133
121,6094,chapter_2_2_3,1st midterm,GPT3,From GPT-3 generated summary,"What must we ensure to prevent an agent from engaging in underintelligent activities?
",We must ensure that we haven,6094
122,5079,chapter_27_1_2,1st midterm,GPT3,From raw text,"Will programs ever be capable of doing all of these things?
",It is unclear whether programs will ever be capable of doing all of these things.,5079
123,70,chapter16_3,midterm_2,GPT3,Best Condition - with Davinci,"What is a solution that is optimal for a risk-seeking agent?
",A solution that is optimal for a risk-seeking agent is one in which the expected payoff is higher than the guaranteed payoff.,70
124,523,chapter12_2,midterm_2,GPT3,GoodSummary,"What are events?
",A set of all worlds in the sample space that satisfy an assertion.,523
125,1673,chapter12_6,midterm_2,GPT3,Fewshot,"4.
",4.,1673
126,6349,chapter_2_4_4,1st midterm,T5,From GPT-3 generated summary,What does a goal-based agent rely on to decide what to do?,goal information,6349
127,6318,chapter_2_2_3,1st midterm,T5,From GPT-3 generated summary,What does our definition of rationality require a rational agent to do?,learn as much as possible,6318
128,2068,chapter6_3,midterm_1,T5,GoodSummary,What do we only check when var X is assigned?,immediate neighbors,2068
129,5128,chapter_2_4,1st midterm,GPT3,From raw text,"What is an agent program?
",An agent program is the program that implements the agent function.,5128
130,988,slp_chapter6_2,midterm_2,GPT3,BadSummary,"This is a very abstract question. 

review what is a word?
","A word is a sequence of one or more letters.

what is the most important difference between a sentence and a word?
",988
131,3276,chapter6_1,midterm_1,T5,Zero,What is the main idea of constraint propagation?,using the constraints to reduce the number of legal values for a variable,3276
132,104,chapter12_2,midterm_2,GPT3,Best Condition - with Davinci,"What is the uppercase greek letter omega (ω) used for?
","The uppercase greek letter omega (ω) is used to refer to the sample space, while the lowercase greek letter omega (ω) refers to elements of the space, particularly possible worlds.",104
133,881,chapter19_2,midterm_2,GPT3,BadSummary,"What is exploratory data analysis?
",Exploratory data analysis is a set of techniques used to determine the best fit function for a set of example inputs.,881
134,5187,chapter_3_3_3,1st midterm,GPT3,From raw text,"3.3.what is a tree-like search?
",3.3.a tree-like search is a search algorithm that does not check for redundant paths.,5187
135,4310,slp_chapter6_10,midterm_2,T5,Fewshot,What model is used to predict the likelihood of a word $w$ appearing near another word $apricot$?,word2vec,4310
136,6219,chapter_1_1_3,1st midterm,T5,From GPT-3 generated summary,In what century did logicians develop a precise notation for statements about objects in the world and the relations among them?,19th,6219
137,6190,chapter_3_4_3,1st midterm,GPT3,From GPT-3 generated summary,"Despite its shortcomings, what is depth-first search still used for?
","Despite its shortcomings, depth-first search is still used in many areas of ai because it has much smaller memory requirements than other algorithms.",6190
138,722,slp_chapter6_11,midterm_2,GPT3,GoodSummary,"What can be used in a historical context to see historical biases?
",Implicit associations can be used in a historical context to see historical biases.,722
139,668,slp_chapter7_2,midterm_2,GPT3,GoodSummary,"What is the limitation of a perceptron when it comes to computing the xor logical operation?
","The limitation of a perceptron when it comes to computing the xor logical operation is that it is a linear classifier, and thus its decision boundary is a line.",668
