Exam 3 Flashcards

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1
Q

Well- and Ill-Defined Problems:

What is a problem? What are its 3 components?

A
  • problem: a situation without an immediately apparent standard or routine way of reaching a goal
  • 3 components:
    1. ) goal state (what you’re working towards)
    2. ) initial state (info you have at start of problem)
    3. ) operators (action you can take to move from initial to goal state)
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2
Q

Well- and Ill-Defined Problems:

What is the difference between a well-defined and an ill-defined problem?

A
  • well-defined: all 3 components are known

- ill-defined: at least one component is undefined/not known; possibly more difficult to solve

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3
Q

Well- and Ill-Defined Problems:

What are Goel’s four stages of ill-defined problem-solving?

A
  • 1.) problem scoping - what problem entails; use knowledge you have to study problem statement
  • 2.) preliminary solution generation - trying to figure out how you’re going to go about finding a solution, path to solution; “lateral transformation”
  • 3.) refinement - how it would look if you took a particular path; “vertical transformation”
  • 4.) detailing of solutions - final commitment to one path/solution
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4
Q

Well- and Ill-Defined Problems:
What is the difference between a lateral transformation and a vertical transformation through problem space, according to Goel?

A
  • vertical: look down a path to see what would happen next, what steps
  • horizontal: comparing choices/options at each move
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5
Q

Well- and Ill-Defined Problems:

What role does the prefrontal cortex play in solving well- vs. ill-defined problems, according to Goel?

A
  • location where the problem mainly occurs
  • hemisphere difference in how approach the problem:
  • left hem. damage: impairs well-defined problem solving
  • right hem. damage: impairs ill-defined problem solving
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6
Q

Well- and Ill-Defined Problems:

What is a problem space? How is it constructed? Describe the tic-tac-toe example

A
  • problem space: visualizing the solving of a problem
  • depict stages of a solved problem or turns in a game as a tree
  • limited by STM (not enough memory for all possible moves)
  • tic-tac-toe: ex. first move of X has 9 choices (branches), second move (next level) is O and has 8 choices
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7
Q

Problem-Solving Strategies and Heuristics:

What is an algorithm? What is a heuristic? What are the advantages/disadvantages of them?

A
  • algorithm: set of procedures that you follow to solve a problem (ex. long division, recipe)
  • advantage of algorithm is if you follow it exactly you won’t make a mistake
  • heuristic: short-cut for how to do something; help you get to solution more quickly
  • advantage of heuristic is it’s quick if you don’t need an exact answer
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8
Q

Problem-Solving Strategies and Heuristics:

What are the heuristics of random guess?

A
  • provides shortcut, gets you kind of closer to the answer
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9
Q

Problem-Solving Strategies and Heuristics:
What are the heuristics of hill-climbing? Discuss how the Rubik’s cube and hobbits and orc problem relate to this type of heuristic

A
  • pick next move to make it look like you’re getting closer to the solution/goal state
  • sometimes looks like you’re moving closer but you may be moving further away from the solution
  • Rubik’s cube problem utilizes this heuristic
  • Hobbits and orcs problem: people have difficulty making a necessary backward move bc it looks like it’s getting them further away from the solution
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10
Q

Problem-Solving Strategies and Heuristics:

What are the heuristics of means-end analysis? How does it relate to the Tower of Hanoi task?

A
  • breaking a big problem down into smaller problems
  • Tower of Hanoi - focus on getting the next ring in goal state
  • efficient to deal with large problems
  • first choice may be significant for next moves but likely don’t realize it
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11
Q

Problem-Solving Strategies and Heuristics:

What is functional fixedness? What are the two classic examples of this?

A
  • functional fixedness: fixated on object’s typical use and cannot see how to use it differently in nontraditional fashion
  • ex. Two String Problem - have to hold two strings but they aren’t long enough, have to use pliers to make a pendulum
  • ex. Candle on the Wall - have to mount a candle onto the wall and only have the candle and a box of tacks to do so
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12
Q

Problem-Solving Strategies and Heuristics:

According to Simon and Newell what are the basic characteristics of the human information-processing system?

A
  • it’s serial (deals with one thing at a time)
  • elementary processes take less than one second
  • inputs and outputs are stored in limited STM
  • LTM has a higher capacity but it’s slower to store info
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13
Q

Problem-Solving Strategies and Heuristics:

Could a computer model solve problems the same exact way that humans do?

A
  • No

- humans are limited by short-term memory

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14
Q

Problem-Solving Strategies and Heuristics:
What is the difference between a “scan and search” strategy and a “progressive deepening strategy”? Which one do people typically use and why?

A
  • “scan and search” - identify most promising node and look ahead before committing to solutions; helps to avoid problems; most efficient strategy
  • “progressive deepening” - look for the shorter path to take through a space, may not look at all nodes or branches
  • ppl use progressive deepening more due to limited STM bc can’t remember all possible outcomes in scan and search
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15
Q

Problem-Solving Strategies and Heuristics:

What info is used to define a problem space?

A
  • task instructions
  • previous experience with similar tasks
  • programs in LTM for such tasks
  • programs in LTM to construct problem spaces
  • information learned while solving the problem
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16
Q

Problem-Solving Applications:

Describe what the Carraher at al study did and found. What mistakes did the children make?

A
  • explore how child street vendors did math on the streets
  • informal task: researchers asked prices on the street in “natural” environment
  • formal task: formal test of mathematical procedures, operation problems, word problems
  • performance overall on formal task wasn’t as good as informal; however did better with word problems then the straight up math problems
  • mistakes: swapped order of operations, incorrect operator, didn’t use operator at all
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17
Q

Problem-Solving Applications:

What does it mean to reason by analogy when it comes to problem solving? How does the Gick and Holyoak study show this?

A
  • reason by analogy: make connections/adapt or modify previous solution to current situation
  • Gick and Holyoak: given problem with solution (fortress/dictator) and given another problem without solution (tumor/doctor)
  • see similarities between the two problems’ elements and adapt existing solution to fulfill current needs
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18
Q

Problem-Solving Applications:

Describe the two examples of real-world problem solving discussed in class

A
  • ex. adapt plastic bottles to act like a light bulb

- ex. nail polish that detects some date-rape drugs

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19
Q

Conditional Reasoning:

What is the difference between conditional, deductive, and inductive reasoning?

A
  • conditional: given conditional statement and extra info
  • deductive: determining whether a conclusion is valid using rules of logic
  • inductive: conclusions you draw are based on probability
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20
Q

Conditional Reasoning:

What is a conditional statement?

A
  • “if then” statement that tells us something about the world
  • antecedent = “if”
  • consequent = “then”
  • only tells us what will happen if antecedent occurs, don’t know what happens if antecedent doesn’t occur
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21
Q

Conditional Reasoning:

What is modus ponens, denial of antecedent, affirmation of consequent, modus tollens?

A
  • modus ponens: told “if” is true, conclude that “then” is true (ex. told he did clean up his toys (“if”), conclude that he got a cookie)
  • denial of antecedent: told “if” is false, conclude “then” is false; invalid conclusion
  • affirmation of the consequent: told “then” is true, conclude if is true, but really an invalid conclusion
  • modus tollens: told “then” is false, conclude “if” is false
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22
Q

Conditional Reasoning:
What is the traditional Wason Selection Task? What cards are people supposed to turn over,? What cards do they actually turn over and why?

A
  • 4 cards, one side number, one side letter
  • “if card has D on one side, then it has a 3 on the other side”
  • should pick D and 7
  • mistake: chose 3 (affirmation of consequent) or D (modus ponens)
  • also task with squiggle cards
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23
Q

Conditional Reasoning:

What is the modified Wason Selection Task? Describe the 3 examples from class

A
  • modified tasks tap into existing schemas so easier to reason with (relevance to real world experiences)
  • ex. “if a person is drinking beer, then they are over 21”
  • ex. “if an envelope is sealed, then it has a 20 cent stamp”
  • ex. “if entering the country, then must have cholera vaccine”
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24
Q

Deduction:

What is a syllogism?

A
  • syllogism: 3 statement set
  • first two statements are premises
  • third statement is a conclusion
  • goal to evaluate if 3rd statement is valid
  • if involves categories of items, then can assess validity using venn diagrams
25
Q

Deduction:

What mistakes do people make when performing deductive reasoning tasks?

A
  • tend to focus on whether it’s true in the real world, rather than validity
  • some things might be true IRL but invalid
  • some things may be false IRL but valid
26
Q

Deduction:

How did Rips study deductive vs. inductive reasoning? What were the results?

A
  • 4 conditions ranging in whether valid/invalid ‘
    A.) deductively correct, causally consistent w/ reality
    B.) deductively correct, casually inconsistent
    C.) deductively incorrect, casually consistent
    D.) deductively incorrect, causally inconsistent
  • C and D did not include the premises so not logical
  • had to rate valid/invalid (deductive) and strength of argument (inductive)
  • results: don’t process validity the same way as strength; deductive and inductive reasoning go through separate processes
27
Q

Induction:

What’s the difference between inductive and deductive reasoning?

A
  • inductive: use info to make a judgement

- deductive: use logic to make decision

28
Q

Induction:

Describe the Mastermind inductive reasoning task

A
  • take in evidence w/ each round
  • don’t know initially correct color or position, so make a hypothesis
  • use the feedback to reformat and work out alternatives
  • keep track of evidence
29
Q

Induction:

Describe the Bruner et. al task rules

A
  • simple rule: one feature
  • conjunctive rule: “and” rule, 2 features, each from a diff dimension
  • disjunctive rule: “or” rule, only need one of 2 parts to be a yes
  • negative rule: “not” rule, pick one feature
  • relational rule: ex. number of shapes matches number of borders
30
Q

Induction:

What rules in the Bruner et. al task are easiest and which are hardest? What strategies are available?

A
  • simple rule is easiest
  • conjunctive is easier than disjunctive
  • strategies:
  • successive scanning: go from yes card and change one feature
  • focus gambling: keep only one feature from something you already know
31
Q

“Rationality” and Reasoning Applications:

What does it mean to be rational or have reason?

A
  • rational thought is:
  • intelligent (based on knowledge)
  • orderly, regular, complete (organizes all info)
  • objective (based on facts not opinion)
32
Q

“Rationality” and Reasoning Applications:

Are people rational? What is the notion of bounded rationality?

A
  • people can be rational in certain circumstances with low cognitive load (and irrational when high cog. load)
  • “bounded rationality” - we can be rational to the extent that our cognitive limitations allow
  • these limitations include attention, working memory, executive functions
33
Q

“Rationality” and Reasoning Applications:

Discuss the first two problems in Tversky and Kahneman’s study

A
  • one group of subjects choose between A and B
  • options were mathematically almost the same except A is absolute/sure while B is risky
  • another group chooses between C and D
  • mathematically same as A and B but framed in terms of lives lost
  • when framed in terms of gains - people pick sure thing
  • when framed in terms of losses - people pick risky choice
  • emotion might play a role
34
Q

“Rationality” and Reasoning Applications:

Discuss problems 3 and 4 in Tversky and Kahneman’s study

A
  • failure to combine decisions
  • 2 sets of 2 options
  • one option sure gain w/ risk, other option sure loss w/ risk
  • should be thinking about combinations
  • people usually treat the sets as separate and choose sure gain then choose loss; not the best outcome
  • problem 4 tells to subjects to think about them together but still treat them as separate
35
Q

“Rationality” and Reasoning Applications:

Discuss problems 5-7 in Tversky and Kahneman’s study

A
  • failure to account for contingencies
  • problem 5: sure gain or risky gain - people choose sure gain
  • problem 6: 25% likelihood of reaching stage to choose C or D - so really no longer a sure thing
  • problem 7: choose between options having already advanced
    for prob. 6 and 7 people still prefer guaranteed wins but don’t take into account the low probability of that win
36
Q

“Rationality” and Reasoning Applications:

Discuss problems 8 and 9 in Tversky and Kahneman’s study

A
  • failure to account for similarity in outcomes
  • problem 8: lost $10 bill, will you still buy $10 ticket; people do
  • problem 9: lost ticket, will you buy $10 ticket; people don’t
  • lose same amount of money either way
  • difference in that in problem 8 the $10 hasn’t been assigned to anything yet
37
Q

“Rationality” and Reasoning Applications:

Discuss problem 10 in Tversky and Kahneman’s study

A
  • $5 savings is dependent on proportion of cost
  • calculator $15 regularly, $10 on sale
  • or $125, regular, $120 on sale
  • people willing to drive 20 minutes to buy the $10 one, they don’t treat $5 as $5
38
Q

“Rationality” and Reasoning Applications:

What is the strawman logical fallacy?

A
  • intentionally misrepresent someone’s argument to make it easier to attack
39
Q

“Rationality” and Reasoning Applications:

What is the slippery slope logical fallacy?

A
  • if we allow this to happen, them this other thing will happen, and other thing will happen
40
Q

“Rationality” and Reasoning Applications:

What is the ad hominem logical fallacy?

A
  • attack on opponent is based on personal characteristics rather than their argument
41
Q

“Rationality” and Reasoning Applications:

What is the gambler’s logical fallacy?

A
  • events occur in “runs,” or that something is due bc it’s been a while, but really events are statistically independent
42
Q

“Rationality” and Reasoning Applications:

What is the bandwagon logical fallacy?

A
  • popularity is taken as a measure to indicate if something is good
43
Q

“Rationality” and Reasoning Applications:

What is the black or white logical fallacy?

A
  • presenting a situation as if there is no middle ground or “gray area”
44
Q

“Rationality” and Reasoning Applications:

What is the appeal to authority logical fallacy?

A
  • trusting an authority figure on a topic of which you know little about
45
Q

“Rationality” and Reasoning Applications:

What is the appeal to nature logical fallacy?

A
  • it it’s natural it’s assumed it is good
46
Q

“Rationality” and Reasoning Applications:

What is the anecdotal logical fallacy?

A
  • using personal stories rather than actual scientific evidence, or giving equal weight to personal stories and evidence
47
Q

“Rationality” and Reasoning Applications:

What is the appeal to emotion logical fallacy?

A
  • using emotion to win an argument rather than actual logic or reason
48
Q

“Rationality” and Reasoning Applications:

What is the tuquoque logical fallacy?

A
  • criticizing the criticizers instead of the argument; answering criticism with other criticism
  • ex. they did it too
49
Q

“Rationality” and Reasoning Applications:

What is the Texas sharpshooter logical fallacy?

A
  • pick bits of data that support point and ignore parts that don’t support it
50
Q

Bayes’ Theorem and the Expected Utility Model:

What is Bayes’ Theorem? What does it allow us to do? Do people follow it when making decisions?

A
  • people don’t follow this
  • allows us to figure out exact probability by combining base rate (prior probability, “H”) with evidence (conditional probability, “E”)
51
Q

“Rationality” and Reasoning Applications:

What are framing effects? What is the certainty effect? The pseudocertainty effect?

A
  • framing effects: how something is worded
  • certainty effect: if framed in terms of gains, people will want the sure thing
  • pseudocertainty effect: no longer a sure thing
52
Q

Bayes’ Theorem and the Expected Utility Model:

What is the Expected Utility Model? Do people follow it when making decisions?

A
  • allows you to figure out which of two options is mathematically better
  • people are motivated to win and may choose the higher prob. of winning
  • gains: prob. of winning x amount to be won
  • loss and gains: (prob. winning x amount to win) - (prob. lose x amount to lose)
53
Q

Decision-Making Heuristics:

What is base-rate neglect?

A
  • ignore given info about statistical probability/likelihood
54
Q

Decision-Making Heuristics:

Describe De Neys et. al’s study

A
  • given description of fictional person and given statistic
  • 4 diff conditions:
  • incongruent: heuristic and probability lead to different choices
  • congruent (control): heuristic and probability lead to same choice ‘
  • neutral (control): cannot use heuristics, must be probability only
  • heuristic (control): cannot use probability, must use heuristic only
  • results: high accuracy for control conditions and in incongruent condition longer response time when used base-rate
55
Q

Decision-Making Heuristics:

What role do the anterior cingulate cortex and right lateral prefrontal cortex play in heuristic decision-making?

A
  • ACC: involved in conflict monitoring; more active in incongruent trials, indicates that subjects detected conflict
  • RLPFC: differences in activity depending on whether selected base-rate or heuristic; more activity with base-rate response
56
Q

Decision-Making Heuristics:

What is the representativeness heuristic?

A
  • how well something fits our idea of something else
  • description much more representative of a certain subset of the group and increases your idea of the likelihood while ignoring the base-rate
57
Q

Decision-Making Heuristics:

What is the availability heuristic?

A
  • assume something happens more often if we can retrieve many memories of that something happening
  • we assume the statistical probability is higher than it actually is
  • ex. media replaying events
58
Q

Decision-Making Applications:
Discuss the Hammerton study. Why did people make those mistakes? How does Bayes’ Theorem help us evaluate the results of medical screenings?

A
  • examined how people use base-rate info to make medical judgments
  • fictional disease and given statements
  • 90% chance person w/ disease will be recorded positive
  • if no disease 1% chance for false positive
  • roughly 1% of pop has disease
  • subjects median response was 85% chance of having disease
  • really should be about 50%
  • confidence ratings very high, even when just guessing without all the given info
  • overall people weren’t using base-rate info - instead maybe used their memory to try to recall instances
    Bayes’ theorem takes into account all statistical probabilities of having the disease, false pos., etc.
59
Q

Decision-Making Heuristics:

Which heuristic is involved when we use media coverage to determine risk or base rate probability?

A
  • availability heuristic