chapter 4: local integration 1: reasoning & evolutionary psychology

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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. - PowerPoint PPT Presentation

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  • 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 rulesModus ponensModus tollensIf p then qIf p then qpnot-qTherefore qTherefore not-p

    Affirming the consequentDenying antecedentIf p then qIf p then qqnot-pTherefore pTherefore not-q

  • Wason selection taskWhat 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 exchangeTwo 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 resultsIf a man is eating cassava root, he must have a tattooed faceEATS CASSAVA ROOTEATS MOLO NUTSTATTOONOTATTOODescriptive versionPoor performance (21%)

    Social exchange versionBetter performance (75%)

  • Cosmides and Tooby analysis

    EATS CASSAVA ROOTEATS MOLO NUTSTATTOONOTATTOOBenefitNo benefitCost paidCost not paidSocial exchange version has following structure

    If BENEFIT then COST

    Cheater = BENEFIT without COST [i.e. p & ~ q]

  • Local integration 1Solution 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 taskStandard 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 ROOTEATS MOLO NUTSTATTOONOTATTOOBenefitNo benefitCost paidCost not paidSwitched social exchange version has following structure

    If COST then BENEFIT

    Logically correct answers are cards 2 and 3Cheater 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 thesisGives 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 prisoners 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 PDPlayer A

    COOPDEFECT

    PlayerCOOP5, 510, 0BDEFECT0, 102, 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

  • Axelrods computer tournamentInvited 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 TIT-FOR-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 1Solution of adaptive problems

    Explains

    Emergence of dedicated cheater detection system

    Explains

    Patterns of error in logical reasoning tasks

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