Towards realistic models for evolution of cooperation
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Towards Realistic Models for Evolution of Cooperation. LIK MUI. … about procedure …. Briefly go over the paper Clarify major points Describe simulations (not in paper). RoadMap. Introduction Cooperation Models Simulations Conclusion. . Evolution of Cooperation. Animals cooperate

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About procedure
… about procedure …

  • Briefly go over the paper

    • Clarify major points

  • Describe simulations (not in paper)


Roadmap
RoadMap

  • Introduction

  • Cooperation Models

  • Simulations

  • Conclusion


Evolution of cooperation
Evolution of Cooperation

  • Animals cooperate

  • Two questions:

    • How does cooperation as a strategy becomes stable evolutionarily?

    • How does cooperation arise in the first place?


Darwinian natural selection
Darwinian Natural Selection

“Survival of the fittest”

  • If evolution is all about individual survival, how can cooperation be explained?

  • Fittest what?


Fittest what
Fittest what ?

  • Individual

    • Rational agency theory (Kreps, 1990)

  • Group

    • Group selection theory (Wilson, 1980)

  • Gene

    • Selfish gene hypothesis (Dawkins, 1979)

  • Organization

    • Classic organizational theory (Simon, 1969)


Roadmap1
RoadMap

  • Introduction

  • Cooperation Models

    • Group Selection

    • Kinship Theory

    • Direct Reciprocity

    • Indirect Reciprocity

    • Social Learning

  • Simulations

  • Conclusion


  • Group selection
    Group Selection

    • Intuition: we ban cannibalism but not carnivorousness

    • Population/species: basic unit of natural selection

    • Problem: explain war, family feud, competition, etc.


    Kinship theory i
    Kinship Theory I

    • Intuition: nepotism

    • Hamilton’s Rule:

      • Individuals show less aggression and more cooperation towards closer kin if rule is satisfied

      • Basis for most work on kinship theory

    • Wright’s Coefficient of Related: r

      • Self: r=1

      • Siblings: r=0.5

      • Grandparent-grandchild: r=0.25


    Kinship theory ii
    Kinship Theory II

    • Cannot explain:

      • Competition in viscuous population

      • Symbioses

      • Dynamics of cooperation


    Direct reciprocity
    Direct Reciprocity

    • Intuition: being nice to others who are nice

    • “Reciprocal Altruism”

      • Trivers (1971)

    • Tit-for-tat and PD tournament

      • Axelrod and Hamilton (1981)

    • Cannot explain:

      • We cooperate not only with people who cooperate with us


    Indirect reciprocity
    Indirect Reciprocity

    • Intuition: respect one who is famous

    • Social-biological justifications

      • Biology: generalized altruism (Trivers, 1971, 1985)

      • Sociobiology: Alexandar (1986)

      • Sociology: Ostrom (1998)

    • 3 types of indirect reciprocity:

      • Looped

      • Observer-based

      • Image-based


    Indirect reciprocity looped
    Indirect Reciprocity: Looped

    • Looped Indirect Reciprocity

      • Boyd and Richerson (1989)


    Indirect reciprocity observers
    Indirect Reciprocity: Observers

    • Observer-based Reciprocity

      • Pollock and Dugatkin (1992)


    Indirect reciprocity image
    Indirect Reciprocity: Image

    • Image (reputation) based Reciprocity

      • Nowak and Sigmund (1998, 2000)


    Social learning
    Social Learning

    • Intuition: imitate those who are successful

    • Cultural transmission

      • Boyd and Richerson (1982)

    • Docility

      • Simon (1990, 1991)


    Critiques of existing models
    Critiques of Existing Models

    • Many theories each explaining one or a few aspects of cooperation

    • Unrealism of model assumptions


    Unrealism for existing models
    Unrealism for Existing Models

    • asexual, non-overlapping generations

    • simultaneous play for every interaction

      • c.f., Abell and Reyniers, 2000

    • dyadic interactions

    • mostly predetermined behavior

      • c.f., May, 1987 (lack of modeling stochasticity)

    • discrete actions (cooperate or defect)

    • social structure and cooperation

      • c.f., Simon, 1991; Cohen, et al., 2001

    • extend social learning

      • c.f., Simon, 1990


    Roadmap2
    RoadMap

    • Introduction

    • Cooperation Models

    • Simulations

      • Nowak and Sigmund Game

      • Prisoner’s Dilemma Game

      • Simon’s Docility Hypothesis

  • Conclusion


  • Nowak and sigmund game
    Nowak and Sigmund Game

    • Payoff Matrix

      C = 0.1

      B = 1.0

    • Image Adjustment

      A = 1






    Evolutionary pd game
    Evolutionary PD Game

    • Repeated Prisoners’ Dilemma Game

    • Agent Actions:

      Action = { cooperate, defect }

    • Payoff Matrix:


    Pd game agent strategies
    PD Game Agent Strategies

    • All defecting (AllD)

    • Tit-for-tat (TFT)

    • Reputational Tit-for-tat (RTFT): using various notions of reputation



    Simple groups social structures
    Simple Groups: social structures

    • Group structure affects members

      • Interactions, observations, and knowledge

      • Persistent structure

    • Groups actions

      • Observed indirectly through member's actions


    Group membership
    Group Membership

    • Member agents

      • Have public group identity

      • Directly associated with one environment

    • Group Structure is a Tree

      • Least common ancestral node (LCAN)

      • Events occur with respect to a shared environment


    Shared environment example
    Shared Environment Example

    AgentsGroup

    A1,A2 G1

    A3,A4 G2

    A5,A2 G1

    A1,A3 G0

    A5,A3 G0


    Pd game with group reputation varying encounters per generation epg
    PD Game with Group Reputation(varying encounters per generation EPG)


    Pd game with group reputation 100 epg varying inter group interaction probability
    PD Game with Group Reputation (100 EPG; varying Inter-group interaction probability)


    Groups organizations bounded rationality explanation
    Groups/Organizations: bounded rationality explanation

    • Docility

      • Cooperation (altruism) as an explanation for the formation of groups/organizations

    • Why individuals “identify” with a group?

      • boundedly rational individuals

      • increase their survival fitness

        (Simon, 1969, 1990, 1991)


    Pd game with docility 50 cooperators and 50 defectors 100 epg 1 0 ip
    PD Game with Docility(50 cooperators and 50 defectors; 100 EPG; 1.0 IP)


    Conclusion
    Conclusion

    • Reviewed 5 major approaches to study evolution of cooperation

    • Provided 2 main critiques for existing models

    • Constructed model extensions addressing the critiques


    Implications for computer science
    Implications for Computer Science

    • Artificial intelligence

      • Benevolent agents are not good enough

        (c.f., multi-agents systems)

      • Learning theory can be used to study evolution of cooperation

    • Systems

      • Improve system design by understanding the dynamics of agents

      • Accountability substrate needed for distributed systems


    Future plan
    Future Plan

    • Extend the simple group social structure

    • Overlapping generations

    • Sexual reproduction

    • Extend social learning using realistic/robust learning model




    Modeling diploid organisms2
    Modeling Diploid Organisms

    One of 2 Child Chromosomes

    Parental Chromosomes


    Simulation demo
    Simulation Demo

    • Recall PD payoff matrix:

    • PD strategies: viewed as a probability vectors

      • Strategy: <PI, PT, PR, PP, PS>

      • TFT: < 1, 1, 1, 0, 0 >

      • AllD: < 0, 0, 0, 0, 0 >

      • AllC: < 1, 1, 1, 1, 1 >

      • STFT: < 0, 1, 1, 0, 0 >


    Simulation a search problem
    Simulation: a search problem

    • Search Optimal PD Strategy

      • Search space: I, T, R, P, S probabilities


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