Decision Making and Problem-Solving Flashcards

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1
Q

What are mental models?

A

Mental representations of possible outcomes of a problem scenario
- Plays a key role in reasoning
Cant think of every solution though
- Take up working memory capacity
- Visualizing mentally
Simulation, of what has happened or predicts the future

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2
Q

What is the constructive nature of memory?

A
  • We reconstruct memories based on stored info
  • Constructs mental models
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3
Q

What is system 1?

A
  • Shared between humans and animals, early evolution
  • Fast, parallel, automatic, unconscious, intuitive
  • Set of sub-system
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4
Q

What is system 2?

A
  • Uniquely human
  • Slow, sequential, conscious and deliberate
  • Makes use of working memory
  • Permits abstract thinking
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5
Q

Wason Selection Task - Abstract version

A

Each card has a letter on one side, a number on the other. Which cards need to be turned over to find out whether the statement is true or false?
- Abstract tasks are harder for people
Influence by system 1
- Search for positive evidence - confirmation bias
- Perceptually match cards, relies on first impressions - matching bias

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6
Q

Wason Selection Task - Concrete version

A

A scenario; Each card has the beverage on one side, the age on the other. Which cards need to be turned over to discover under-age drinker breaking the rule?
- Easier to do the right switches
Can give a false sense of right , previous knowledge can impede logical reasoning

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7
Q

Conditional reasoning

A

If P, then Q
- Consists of antecedent and consequence
- Modus Ponens: Affirms the antecedent
- Modus Tollens: Denies the consequents

Its simple but not intuitive
- Connection to hypothesis testing
Prove the null-hypothesis(“if”- part) wrong

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8
Q

Valid arguments

A

Only modus ponens and tollens can lead to a true conclusion according to the rules of logic

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9
Q

Syllogistic Reasoning

A

A combination of two premises and one conclusions
- Categorical syllogism
- Linear syllogism
- Valid conclusions follow the premises
- Easy to get influenced by whats believable or not
Logic isnt based on reality

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10
Q

What does “some” mean in syllogistic reasoning?

A

At least one and possibly all
- Helpful to draw to see the connections
- Should only be one alternative

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11
Q

What can influence acceptance of conclusions?

A
  • Logical reasoning - System 2
  • Prior beliefs, prior knowledge, perceptual matching - System 1
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12
Q

Belief bias

A

Tendency to confirm prior beliefs, especially with logically invalid conclusions
- Interference
- Has to sometimes ignore the meaning of the text

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13
Q

What is inductive reasoning?

A
  • Search for generalizations based on individual observations
  • We can never confirm a hypothesis on the basis of observation and induction
    One discrepant observation results in rejection of the hypothesis
  • Often search for falsification to reject the null-hypothesis
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14
Q

Judgement

A

Determine likelihood of an event or outcome based on incomplete data

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15
Q

Decision

A

Select from different options
- Yes or No

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16
Q

Semantic congruity effect

A

Mental comparison
Reaction time is faster or judgement are faster when the basis of judgment is congruent or similar to the stimuli being compared
The time to select the shorter of two relatively short lines is faster than the time to select the longer one

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17
Q

Distance Effect

A

The greater the distance between the two stimuli in comparison, the faster the decision that they differ
- Works for symbolic values as well
Comparison between two mental symbols
- The just noticeable difference

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18
Q

Snarc Effect

A

Faster responses with left hand to the smallest numbers in the series
Faster responses with right hand to the larger numbers in the series
- Not only numbers
- Cultural differences

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19
Q

How can Snarc Effect be explained?

A
  • We represent numbers on a mental number line from left to right
    How we save info in our memory
  • We place incoming items from left to right in working memory, linked with visuo-spatial sketchpad (its involved)
    Same tendencies in blind people as well
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20
Q

Algorithm

A
  • Specific formula or method
  • Systematic
    Handshakes
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21
Q

Heuristics

A
  • A rule of thumb
  • Informal
  • A strategy or approach that works under some conditions but not others
    Flipping a coin
  • Often during uncertainty
  • Probabilistic reasoning
    Intuitive judgments
22
Q

Research from Kahneman & Tversky

A
  • Presented descriptions of people, who are more likely to be in a certain profession
  • Interested in how people predict likelihood, categorize events and bias / errors
23
Q

Representative Heuritics

A

Estimate of probability or likelihood of an event is determined by how similar the event is to the class of events it came for

24
Q

What can influence representative heuritics?

A
  • Additional information that is consistent with prior knowledge or beliefs
    Conjunction fallacy- easier to pick the option that adds information even if its not logical
  • Insensitivity to sample sizes
    The hospital
  • Stereotypes
    When its about descriptions of people
25
Q

Conjunction Fallacy

A

The more specific category considered as more probably than the related, more general categories
Linda is a bank teller
Linda is a bank teller and is active in the feminist movement

26
Q

Availabilty Heuristic

A

Estimate of probability or likelihood of an event is determined by the ease with which relevant examples can be retrieved from memory
- What happens more frequently or more available in memory
Influences from media

27
Q

What can influence availability heuristics?

A
  • General knowledge
  • Familiarity
    Ease of recall
  • Salience/Vividness
    Dramatic events
28
Q

Simulation Heuristic

A

Computer based
- Prediction on future events
Finding other outcomes

29
Q

Counterfactual reasoning

A

Line of reasoning goes against a fact in a “what if” scenario
- Seldom focuses on the cause of the event
Victim blaming - Car crash

30
Q

Downhill Change

A

Alter an unusual story element to something more normal

31
Q

Hindsight Bias

A

Affect our memory of events

32
Q

Is heuristics all that bad?

A
  • Not necessarily
    People use it because they lead to successful behaviour
  • Guiding behaviour
33
Q

Recognition Heuristic

A

If one of the two alternatives is recognized and the other is not, then infer that the recognized alternative has the higher value with respect to the criterion
- Which city is larger?
- Having a reference point influences your decision

34
Q

Satisficing Heuristis

A

“Good enough”

35
Q

Take-the-best Heuristic

A

If you know both names, you create other alternatives on which you base your decision of

36
Q

What is a problem?

A

A time consuming task that requires a series of intermediate steps to solve the problem

37
Q

What conditions does problem-solving require?

A

Two distinct states of affairs
The agent is in one state and wants to be in the other state
It is not apparent to the agent how the gap between the two states is to be bridged
Bridging the is a consciously guided multi-step process

38
Q

How do they collect data?

A

Through verbal protocol

39
Q

Gestalt

A

A whole pattern, a form or a configuration
- A cohesive grouping

40
Q

Means-end heuristic

A

Problem is solved by repeatedly determining the difference between the current state and the sub-goal state, then finding and applying an operation that reduces this difference
- A starting point and an end point
- “Normal” problem-solving method

41
Q

Problem space

A
  • Goals and sub-goals
  • Previous knowledge from the problem solver
42
Q

Operators

A

Legal operations or moves that can be performed

43
Q

Well-defined problems

A

Give explicit and complete specification of all aspects of the problem
- The tower of Hanoi

44
Q

Ill-defined problems

A

Vague specification of the different aspects of the problem
“Just fix it”
- In many real world problems

45
Q

Functional Fixedness

A

Tendency to use objects or concepts in the problem environment in only their customary and usual way
- More familiarity with an object makes it harder to think outside the box
The candle problem
- Identifying objects you can use to cover an egg, objects that you could use to play catch
The objects used in task 1 is rarely used in task 2

46
Q

Negative set

A

Tendency to solve problems in a particular way, using a single specific approach, even when a different approach might be more productive
- Developing a certain algorithm after a couple of problems
- Experts are more prone for this bias

47
Q

What is insight?

A

An “aha” experience - occurs when a person suddenly reinterprets a problem to produce a solution
- Critical inference
- Outcome from overcoming negative set or functional fixedness
- Can come from an analogy

48
Q

What is an analogy?

A

The current problem is similar to an already-solved problem
- Finding similarities
- Using analogies to solve problems is not an automatic process

49
Q

Incubation

A

Difficult with a problem, stop working on it and a solution may come later
- Often with misleading information

50
Q

What did the study by Metcalfe & Wiebe find?

A
  • People are accurate in predictions in solving issues with routine problems, but not with insight problems
51
Q

Multiconstraint Theory - Holyoak & Thagard

A

Predicts how well people use analogies in problem solving and factors in those analogies
- Similarities between source domain and target domain
- Problem structure, is there any parallel structure?
- Purpose of the analogy, a persons goal and problem goal

Focuses on explicit use of analogies

52
Q

How can you improve problem-solving?

A
  • Domain knowledge
  • Automatic some components
  • Systematic plan
  • Draw inferences
  • Develop sub-goals
  • Work backwards
  • Search for contradictions
  • Relations between the problems at hand
  • Think outside the box
  • Stay calm
  • Practice