Transcript Local integration 1

Chapter 4:
Local integration 1: Reasoning &
evolutionary psychology
Overview
• Introduce experimental data from psychology of
reasoning
• Outline how these data have been interpreted by
evolutionary psychologists
• Draw out some implications for thinking about
the integration challenge
Psychology of reasoning
• Psychologists have produced evidence that
subjects regularly contravene basic principles of
deductive logic probability theory when engaged
in
• conditional reasoning
• judgments of likelihood
Conditional reasoning rules
Modus ponens
If p then q
p
Therefore q
Modus tollens
If p then q
not-q
Therefore not-p
Affirming the consequent
If p then q
q
Therefore p
Denying antecedent
If p then q
not-p
Therefore not-q
Wason selection task
What cards need to be turned over to evaluate:
If a card has a vowel on one side then it has an
odd number on the other side
Cassava root studies (Cosmides and
Tooby)
Background about (imaginary) Pacific island:
• Only married men have facial tattoos
• Cassava roots are a highly prized delicacy and
aphrodisiac
• Molo nuts are bitter and not valued in the
community
Social exchange
Two versions of cassava root story
Descriptive: married men live on the side of the
island where cassava roots grow, while
unmarried men live on the side where the molo
nuts grow
Social exchange: only married men have the
right to eat cassava roots.
Test and results
•If a man is eating cassava root, he must have a
tattooed face
EATS
CASSAVA
ROOT
EATS
MOLO
NUTS
TATTOO
NO
TATTOO
Descriptive version
Poor performance (21%)
Social exchange version
Better performance (75%)
Cosmides and Tooby analysis
EATS
CASSAVA
ROOT
•
Benefit
EATS
MOLO
NUTS
No benefit
TATTOO
Cost paid
NO
TATTOO
Cost not paid
Social exchange version has following structure
If BENEFIT then COST
Cheater = BENEFIT without COST [i.e. p & ~ q]
Local integration 1
•Solution of adaptive problems
Explains
•Emergence of dedicated cheater detection system
Explains
•Patterns of error in logical reasoning tasks
The structure of the argument!!
•If CONDITIONAL REASONING EXPLOITS A CHEATER
DETECTION MODULE (p) then PERFORMANCE WILL
BE BETTER ON THE SOCIAL EXCHANGE VERSION (q)
•PERFORMANCE IS BETTER ON THE SOCIAL
EXCHANGE VERSION (q)
•Therefore, CONDITIONAL REASONING EXPLOITS A
CHEATER DETECTION MODULE (p)
Switched selection task
Standard social exchange selection task
• If BENEFIT (p) then COST (q)
• violation = p and not-q
Switched social exchange selection task
• If COST (p) then BENEFIT (q)
• violation = q and not-p
• Subjects typically give the logically correct answer on the standard
version, but not on the switched version
• Detecting a violation of the switched version is not the same as
detecting a counter-example to the conditional
Cosmides and Tooby analysis
EATS
CASSAVA
ROOT
•
Benefit
EATS
MOLO
NUTS
No benefit
TATTOO
Cost paid
NO
TATTOO
Cost not paid
Switched social exchange version has following structure
If COST then BENEFIT
Logically correct answers are cards 2 and 3
Cheater detection answers remain 1 and 4
Evolutionary psychology and
conditional reasoning
• evolutionary psychologists reject the idea of domain-general
reasoning skills
either mental logic or mental models
• suggest that we employ context-dependent inference rules – in
particular, rules for detecting cheaters in social exchanges
• integrate these experimental data with a model of how the mind is
organized and how it evolved
Massive modularity thesis
Gives a picture of the overall organization of the mind
• mind composed of highly specialized cognitive
modules (Darwinian modules)
• each module evolved to solve a particular
adaptive problem
• each module exploits specialized rules that are
domain-specific
• No domain-general “central cognition” or
abstract reasoning mechanism
Cheater detection module
The Cosmides/Tooby experiments seem to show
specialized skills for cheater detection
• not simply specialized skills for conditional
reasoning involving social exchanges
These experimental results are integrated with the
massive modularity hypothesis via an evolutionary
explanation of why there needs to be a cheater detection
module
• evolutionary explanation itself grounded in an
account of the evolution of altruism
The puzzle of altruistic behavior
• Cooperative behavior widespread in animal kingdom
• even in lower animals ants, termites, bees etc (individuals
fed by others etc)
• not restricted to kin
• Cooperative behavior presumably has a genetic basis
• But how did the genes coding for cooperative behavior ever get
established in the gene pool?
• natural selection seems to favor “selfish”
behavior - free riders can always exploit altruists
Modeling the evolution of cooperation
The prisoner’s dilemma is a very useful tool for modeling the
problem
• we can assume that participants are purely
selfish
• set up so that cooperation is not the dominant
strategy for
• can easily be extrapolated to multi-person
interactions (tragedy of the commons)
One-shot PD
•
Player A
•
•Player
•B
•
COOP
DEFECT
COOP
5, 5
10, 0
DEFECT
0, 10
2, 2
•Illustrates basic structure of interactions where being a free
rider is advantageous
Decision-making in a one-shot PD
• Work backwards from what the other agent might do
• Look at your options if the other agent
cooperates – it is best for you to defect
• Look at your options if the other agent defects –
it is best for you to defect
•The dominant strategy for each play is DEFECT
•But mutual defection is sub-optimal
Iterated PDs
• A backwards induction argument shows that DEFECT is
dominant when the number of plays is known
• But for modeling the evolution of cooperation the
interesting case is the indefinitely iterated PD
• opens up possibility of strategies that “punish”
other player for defecting
• and “rewarding” for cooperating
Axelrod’s computer tournament
Invited game theorists to submit strategies for iterated PD
tournament
• played strategies against each other for around
200 iterations
Highest average score came from TIT-FOR-TAT
• Start by cooperating
• Then do what the opponent did on the previous
round
TIT-FOR-TAT
• Shows how cooperative behavior might emerge in very
simple organisms
• and be maintained since, in the right conditions,
it is an evolutionarily stable strategy
• Some evidence that TIT-FOR-TAT is followed in the animal
kingdom (3-spined sticklebacks)
• Has been used to model complicated human interactions
(e.g. voting patterns in US Senate)
Back to cheater detection
• TIT-FOR-TAT (or some similar strategy, such as TITFOR-TWO-TATS) can only work if there is a reliable
mechanism for detecting cheaters. . .
• Evolutionary pressure for selection of cheater detection
module
• According to Cosmides and Tooby, this module explains
the pattern of choices made in conditional reasoning tasks
Local integration 1
•Solution of adaptive problems
Explains
•Emergence of dedicated cheater detection system
Explains
•Patterns of error in logical reasoning tasks