Module 4 Flashcards

(48 cards)

1
Q

What is the distinction between
system 1 and system 2 thinking?

A

Fast, Intuitive, & Instinctive vs Slow &
Rational

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2
Q

How can the process of problem
solving be explained by this “space”
analogy?

A

Search through a space
toward a goal - Initial state,Goal state, Operators, Constraints

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3
Q

What is the distinction between
algorithms and heuristics?

A

A procedure that, if followed correctly, guarantees that one reaches the goal state vs. A “rule of thumb” for fast solving problems with no guarantee

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4
Q

How can well-defined be
differentiated from ill-defined
problems?

A

Whether or not the key elements of a problem space (= initial state, goal state, operators, & constraints) can be specified

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5
Q

What are the common “stumbling
blocks” to problem solving?

A
  • Failure to select/use appropriate
    heuristics
  • Inappropriate mental set and functional fixedness
  • Incorrect or incomplete representations of the problem
  • Lack of relevant domain-specific
    knowledge
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6
Q

hill climbing & working backward heuristics

A

trying to always move closer to
the goal state
- Multiple operators = choose the
one that moves you in the direction of the goal state

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7
Q

inappropriate mental set

A

A preconceived notion about how to approach a problem based on a person’s experience or what has worked in the past

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8
Q

functional fixedness

A

An effect that occurs when the ideas a person has about an object’s function inhibit the person’s ability to use the object for a different function

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9
Q

Tower of Hanoi problem solving

A

well defined problem - hill climbing

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10
Q

the water lilies problem in problem solving

A

working backwards - Analyzing the goal state to determine the last step needed to achieve it, then the next-to-last step

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11
Q

How are deductive reasoning and
inductive reasoning different from each other?

A

Drawing a logically certain and specific conclusion from a set of general premises (general to specific)
vs.
Reaching a probable general conclusion, based on a set of specific facts (specific to general) (specific hypothesis)

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12
Q

What are the two valid and two invalid inferences for conditional reasoning, according to formal logic?

A

Logically valid inferences
◦ Modus ponens
◦ Modus tollens
Logically invalid inferences
◦ Denial of the antecedent
◦ Affirmation of the consequent

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13
Q

In what ways does human conditional reasoning deviate from formal logic?

A

Applying formal logic rules ensures valid conclusions
- humans do not always follow formal logic
- difficult to apply modus tollens
- invalid inferences
- Example: card selection task

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13
Q

what roles do concrete contexts play in human conditional reasoning?

A

Detecting “cheaters” (those who violate social contacts) has evolutionary significance

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14
Q

modus ponens

A

If P then Q
P
Therefore Q

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15
Q

modus tollens

A

If P then Q
~Q
Therefore ~P

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16
Q

affirmation of the consequent

A

If P then Q
~P
Therefore ~Q

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17
Q

denial of the antecedent

A

If P then Q
Q
Therefore P

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18
Q

Wason’s card selection task

A

If a card has a vowel on oneside, then it has an even number on the other side - you need to flip 2 cards: the vowel(E) and the odd card(7)

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19
Q

What are “normative” models?

A

Models that define ideal performance under ideal circumstances in making decisions

20
Q

What are utility theories of decision
making, and how do they work?

A

have served as normative models in decision making research. They are the (subjective) value associated with
a particular circumstance to weigh the pros and cons

21
Q

In what ways are utility theories of decision making limited in characterizing human decision making?

A

Under many situations, utility theories do NOT FULLY describe human decision making:
- Framing effect
- loss aversion

22
Q

What is loss (risk) aversion? How
does it influence our everyday
judgments?

A

Predictions from utility theories are sometimes violated because people
show a clear tendency for avoiding loss

23
Q

What is the framing effect? How does it influence our everyday judgments?

A

The way in which alternatives are
stated (or “framed”) can affect people’s preferences:
- discount vs surcharge
- opt-in vs opt-out

24
expected utility theory
people choose options by calculating the potential value Expected utility = (utility of the outcome) x (probability of the outcome)
25
multiattribute utility theory
It is about choices involving multiple alternatives with multiple attributes: [(weighting of attribute 1 ) x (utility rating of attribute1 )] + [(weighting of attribute2 ) x (utility rating of attribute2 )]...
26
llustrative decision examples for the framing effect and loss aversion
Framing effect: Discount” vs. “surcharge” (the gas station example) * “Opt-in” vs. “opt-out” procedures (organ donations & cookie consent management) Loss aversion: Basic assumption, Humans are rational, consistent decision makers taking all factors into account
26
What are some of the biases resulting from the use of each decision-making heuristic identified by Tversky & Kahneman?
biased judgments, arbitrary judgements, stereotyping
26
What are the major decision-making heuristics identified by Tversky & Kahneman’s pioneering work?
- The availability heuristic - The anchoring and adjustment heuristic - The representativeness heuristic
27
What are other common biases affecting human thinking? Can you come up with everyday examples?
bias your decisions, biased judgments, arbitrary judgements,
28
Is human decision making rational? What is Herbert Simon’s take on this rationality question?
Is better to “satisfice” than “optimize” - notion of bounded rationality, simple and quick
29
availability
A strategy based on how easily you can recall relevant examples
30
anchoring & adjustment
A strategy in which: one begins with a first approximation(anchoring) and then makes appropriate adjustments based on additional information
31
representativeness
A strategy that focuses on how representative the item or event is of the target population
32
base rate neglect
conjunction fallacy, ignore general statistical information
33
conjunction fallacy
a reasoning error where a person believes a combination of two events is more probable than one of the individual events alone
34
small-sample fallacy
An erroneous belief that small samples can be as equally representative of the target population as large samples
35
law of large numbers
Larger samples a more representative of the population than smaller samples do
36
gambler’s fallacy
instance of small-sample fallacy, belief that an event that has not occurred for some time is more likely to occur soon
37
optimism bias
Overestimating what the future self can accomplish
38
negativity bias
Negative evidence having disproportionately more impact on one’s decision than positive evidence
39
confirmation bias
The tendency to look for information that supports (rather than rejects) one’s preconceptions
40
hindsight bias
Believing, after an event has already happened, that the event had been inevitable and was predicted all along
41
sunk-cost bias
expending additional resources to justify some previous commitment that has not worked well
42
satisficing
Is better to “satisfice” than “optimize” * “satisfy” + “sacrifice”
43
heuristic-related biases
vailability bias or the representativeness heuristic
43
bounded rationality
the idea that decision-making is limited by cognitive constraints, time, and the information available, causing people to make "good enough" or satisficing decisions instead of the optimal ones
44