Week 10 - Problem solving, reasoning, decision making Flashcards
Patient PF
- His right anterior prefrontal cortex was damaged due to a stroke
- Successful architect before the stroke
- He seemed perfectly normal and intelligent
- However, he lost his ability in architectural design
Operator
An action that will transform the problem state into another problem state
start state -> operators -> goal state
problem space
problem space consists of various states of the problem
problem state
A representation of the problem in some degree of solution
problem solving
searching a sequence of states in a problem space that goes from the start state to the goal state
Three ways to acquire new operators?
- discovery
- direct instruction
- analogy/imitation
Operator selection
- backup avoidance
- difference reduction
- means-ends analysis
backup avoidance
The tendency in problem solving to avoid operators that take one back to a
state already visited
difference reduction
- The tendency in problem solving to select operators that eliminate a difference between the current state and the goal state
- It is a useful method, but not always optimal
- It only considers whether the next step is an improvement and not whether the larger plan will work
Means-ends analysis
- creates a new subgoal to enable an operator to apply (an operator is not abandoned even if it cannot be applied immediately)
- identifies the biggest difference between the current state and the goal state and try to eliminate it first
- tower of hanoi problem
Observations of Tower of Hanoi problem
- Difference reduction doesn’t allow you to solve the Tower of Hanoi problem
- People tend to adopt the difference reduction strategy first and then start using
means-ends analysis when they try to solve the Tower of Hanoi problem - Patients with prefrontal damage often have difficulty in making backward moves
in the Tower of Hanoi problem - They cannot maintain the goal in working memory very well
problem presentation
- How states of a problem are represented has significant effects
- Successful problem solving depends on representing problems in a way appropriate operators can be applied
Incubation effects
- The phenomenon that sometimes solutions to a particular problem come easier after a period of time in which one has ignored trying to solve the problem
- Incubation effects occur because people forget inappropriate ways of solving
problems
Silveira’s (1971) cheap-necklace problem
Three groups of participants (they all worked on the problem for 30 min)
* Control: continuous 30 min (55%)
* Group 1: interrupted by 30-min of other activities (64%)
* Group 2: interrupted by a 4-hour break (85%)
four areas of human irrationailty
- Reasoning about conditionals
- Reasoning about quantifiers
- Reasoning about probabilities
- Decision making
What is a conditional statement
- If A, then B
- An assertion that if an antecedent (A) is true, then a consequent (B) must be true
Wason selection task
- If a card has a vowel on one side, then it has an even number on the other side
- Neither a vowel nor a consonant on the other side of 4 will falsify the rule
- only 10% of participants made the right combination choices
Permission schema
performance on a selection task can be enhanced when the material has meaningful content
Griggs and Cox (1982)
- if a person is drinking a beer, then the person must be over 19
- 74% of participants selected the logically correct combination
Probabilistic interpretation
- people tend to select cards that will be informative under a probabilistic model, not a strict logical model
- If A, then B (B will probably occur when A occurs)
Oaksford and Chater (1994) car task
- “If a car has a broken headlight, it will have a broken taillight.”
Given four choices: - cars with broken headlights
- cars without broken taillights
- cars without broken headlights
- cars with broken tailights
first two are the logically correct choices
probabilistic interpretation of the car task
- It is not logical, but informative choice
- We tend to interpret conditional statements on the basis of a probabilistic model, not a strict logical model
- because doing so actually makes sense in many situations in real life
- This might be one reason why making the correct (=logical) choice in the original
Wason’s selection task is so difficult
Prior probability
The probability that a statement is true before consideration of the evidence
Posterior probability
- The probability that the statement is true after consideration of the evidence
- To calculate the posterior probability, you need to take into account:
- Prior probability (base rate)
- Evidence
- How reliable the evidence is
Bayes’s theorem computes the posterior probability
Base-rate neglect
people often fail to take base rates into account in making probability judgement
Hammerton (1973) probability study
- Suppose you take a diagnostic test for a rare form of cancer
- Only 1 in 10,000 people has this cancer
- This cancer results in a positive test 95% of the time
- If a person does not have the cancer, the probability of a positive result is 5%
Judgements of probability/frequency
We can be biased in our estimates of probabilities when we must rely on
factors such as memory and similarity judgements
Tversky and Kahneman (1974) english words
Participants estimated the proportion of English words:
* that begin with k (e.g., kettle)
* with k in the third position
- They estimated that more words begin with k than have it in the third position
- 3x as many words have k in the third position than begin with k
Decision making
subjective utility
- the subjective value someone places on something
- it usually forms a non-linear function
- the subjective value tends to decrease more steeply in negative direction
