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Groupwise information sharing
        promotes ingroup favoritism
           in indirect reciprocity
               Mitsuhiro Nakamura & Naoki Masuda
              Department of Mathematical Informatics
                   The University of Tokyo, Japan


M. Nakamura & N. Masuda. BMC Evol Biol 2012, 12:213
http:/www.biomedcentral.com/1471-2148/12/213           1
Indirect reciprocity
                       Alexander, Hamilton, Nowak & Sigmund

▶   A mechanism for sustaining cooperation

        Cost of help                  Benefit
                       !!     "#

                              "#
                                      Later, the cost of
                                     help is compensated
                                        by others’ help
                                                              2
What stabilizes cooperation
  in indirect reciprocity?
1. Apposite reputation assignment rules
2. Apposite sharing of reputation information
   in the population




                                                3
Reputation assignment rules
                   Image scoring (IM)

Donor’s action:                             Recipient’s
cooperation (C)          G    B             reputation:
or defection (D)                        good (G) or bad (B)
                    C    G   G
                    D    B    B

▶   C is good and D is bad
▶   Not ESS (Leimar & Hammerstein, Proc R Soc B 2001)
                                                              4
Reputation assignment rules
Simple standing (ST)           Stern judging (JG)

      G    B                       G   B      C toward a
                                             B player is B!
C     G    G                   C   G   B
D     B    G                   D   B   G
               D against a B               D against a B
                player is G                 player is G

▶   ESS (e.g., Ohtsuki & Iwasa, JTB 2004)                     5
What stabilizes cooperation
          in indirect reciprocity?
      1. Apposite reputation assignment rules
      2. Apposite sharing of reputation information in
         the population

             Incomplete            Group structure
         information sharing       (not well-mixed)
               ignored                 ignored

▶   We assumed groupwise information sharing and
    (unexpectedly) found the emergence of ingroup
    favoritism in indirect reciprocity                   6
Ingroup favoritism
                             Tajfel et al., 1971


▶   Humans help members in the same group (ingroup)
    more often than those in the other group
    (outgroup).
▶   Connection between ingroup favoritism and
    indirect reciprocity has been suggested by social
    psychologists (Mifune, Hashimoto & Yamagishi, Evol
    Hum Behav 2010)


                                                         7
Explanations for ingroup favoritism

▶   Green-beard effect (e.g., Jansen & van Baalen, Nature 2006)
▶   Tag mutation and limited dispersal (Fu et al., Sci Rep 2012)
▶   Gene-culture co-evolution (Ihara, Proc R Soc B 2007)
▶   Intergroup conflict (e.g., Choi & Bowles, Science 2007)
▶   Disease aversion (Faulkner et al., Group Proc Int Rel 2004)
▶   Direct reciprocity (Cosmides & Toobey, Ethol Sociobiol
    1989)
▶   Indirect Reciprocity (Yamagishi et al., Adv Group Proc 1999)
                                                                   8
Model
▶   Donation game in a group-
    structured population
    (ingroup game occurs with
    prob. θ)
                                              "$
▶   Observers in each group
    assign reputations to players
    based on a common               !!   "#

    assignment rule                                "#
                                         "#
▶   Observers assign wrong
    reputations with prob.
    µ << 1                                              9
Reputation dynamics

d                                                                       
                                                                           M
    () = − () +                      θ (  ) + (1 − θ)− (  )                    
                                                                             Φ  (σ ( )   )
d
                              ∈{GB}M                                       =1

  ▶     where,                                                                         r=(G,G,B)
 ()         Prob. that a player in group k has reputation vector r in
                                the eyes of M observers
                                                              Group 3
− () ≡               ()/(M − 1)
                                                                                       $

                                                                        Group 1             Group 2
                =                                                         !!   #

σ ()          Donor’s action: σ (G) = C σ (B) = D                               #        #



Φ (   )     Prob. that an observer assigns r when the observer
      scalar    observes action a toward recipient with reputation r’                              10
Ingroup reputation dynamics
d                                                                   
                                                                       M
    () = − () +                  θ (  ) + (1 − θ)− (  )                    
                                                                         Φ  (σ ( )   )
d
                          ∈{GB}M                                       =1




d                                                       
   in () = −in () +       θin ( ) + (1 − θ)out ( ) Φ (σ (  )   )
                                                       
d                         ∈{GB}




                                                                                            11
Outgroup reputation dynamics
d                                                                                   
                                                                                       M
    () = − () +                                  θ (  ) + (1 − θ)− (  )                    
                                                                                         Φ  (σ ( )   )
d
                                        ∈{GB}M                                                         =1



d                                              
   out () = −out () +
d
                                  ∈{GB}   ∈{GB}
                                                                                                                 
                                                       1                                 1
              θin (  )out (  ) + (1 − θ)           out (  )in (  ) + 1 −        out (  )out (  ) Φ (σ (  )   )
                                                     M −1                              M −1




                                                                                                                                      12
Results: Cooperativeness and ingroup bias
         Frac. G        Frac. G                     Ingroup
        (ingroup)     (outgroup)      Prob. C         bias


 Rule   ∗ (G)
         in            ∗ (G)
                        out              ψ             ρ
           1             1       1
 IM        2             2       2
                                                       0
                          1+θ      µ                   µ
 ST      1−µ          1−µ      1−
                           θ       θ                   θ
                         1    1+θ                    1
 JG      1−µ                      − µθ                 −µ
                         2     2                     2
               ψ ≡ θ∗ (G) + (1 − θ)∗ (G)
                     in              out     ρ ≡ ∗ (G) − ∗ (G)
                                                  in       out
                                                                   13
Results: Individual-based simulations
                                                                                                                                                            (a)
                                                                                                                                                                  1

                              IM                                                                                              ST                            ψ
                                                                                                                                                                                    ST, theory
     1.0




                                                                                       1.0
                                                                                                                                                                0.5                 ST, M = 2
                                                                                                                                                                                    ST, M = 10
     0.8




                                                                                       0.8
Player




                                                                                                                                                                Prob. C             JG, theory
     0.6




                                                                                       0.6                                                                                          JG, M = 2
     0.4




                                                                                       0.4




                                                                                                                                                                  0                 JG, M = 10
     0.2




                                                                                       0.2




                                                                                                                                                                      0       0.5            1
                                                                           JG
     0.0




                                                                                       0.0




                        Group
           −0.2   0.0   0.2   0.4   0.6   0.8      1.0         1.2                             −0.2         0.0         0.2   0.4   0.6   0.8   1.0   1.2




                                                                                                                                                                              θ
                                                                                                                                                            (b)
                                          1.0




                                                                                                                                                             0.5
                                          0.8




           G
                                          0.6




           B                                                                                                                                                ρ
                                          0.4




                                                                                                                                                            0.25
                                                                                                                                                                          Ingroup bias
                                          0.2
                                          0.0




                                                −0.2     0.0         0.2   0.4   0.6     0.8          1.0         1.2




    N=300, µ=.01,                                                                                                  N=103, µ=.01                                   0
     M=3, θ=.6                                                                                                                                                        0       0.5            1
                                                                                                                                                                                                 14
                                                                                                                                                                              θ
Results: Cases with error in actions
                                   (a)
                                         1

                                   ψ
▶   Donors fail in cooperation         0.5
                                                           ST, theory
                                                           ST,  = 0.01
    with prob. ε                       Prob. C
                                                           ST,  = 0.1
                                                           JG, theory
                                                           JG,  = 0.01
                                         0                 JG,  = 0.1

                                             0       0.5              1
                                                      θ
                                   (b)
                                    0.5

                                   ρ
                                   0.25
                                                 Ingroup bias

              N=103, µ=.01, M=10         0

                                             0       0.5              1
                                                                          15
                                                      θ
Results: Evolutionary stability
▶   Conditions under which players using reputations
    are stable against invasion by unconditional
    cooperators and defectors:
    ST
              1          public reputation: θ = 1
         1 
             1−θ         private reputation: θ → 1/M, M → ∞

    JG
            (M−1)(1+θ)         M−1                       1
          1+(M−3)θ+Mθ 2
                            1−Mθ      if 0 ≤ θ        M
            (M−1)(1+θ)
          1+(M−3)θ+Mθ 2
                                      if   1
                                              M   ≤θ≤1
                  1
             →        (M → ∞)
                  θ                                           16
Results: Mixed assignment rules
▶   Observers use JG with prob. α and ST with prob. 1-α
    a                                  b                             c
          1                                0.5                                 5
                                                                                    M2
                                                                                    Θ  0.6
     Ψ                                     Ρ                                   4




                                                                         bc
      0.5                                 0.25                                 3
                   M  2, Θ  0.6
                   M  , Θ  0.6
                   M  2, Θ  0.2                                              2
                   M  , Θ  0.2
          0                                    0                               1
           0             0.5         1          0             0.5    1          0             0.5    1
          ST              Α         JG         ST              Α    JG         ST              Α    JG

    d                                  e                             f
          5                                    5                               5
               M                                  M2                             M
               Θ  0.6                              Θ  0.2                         Θ  0.2
          4                                    4                               4
    bc




                                         bc




                                                                         bc
          3                                    3                               3

          2                                    2                               2

          1                                    1                               1
           0             0.5         1          0             0.5    1          0             0.5    1
          ST              Α         JG         ST              Α    JG         ST              Α    JG   17
Results: Heterogeneous assignment rules
▶    Different groups use different rules (either ST or JG)
                                 (a)                                      (b)
                                    1                                        1
                ψST , ψJG , ρST , ρJG
                                                ψST   ρST                            ψST   ρST
                                                ψJG   ρJG                            ψJG   ρJG
                                    0.5                                   0.5



                                        0                                   0

                                            0     2         4    6    8          0     5     10     15   20

                                 (c)                                      (d)
                                  0.2                           M=8        0.2                    M=20
                                                b=2                                  b=2
                                                b=4                                  b=4
                πJG − πST




                                    0.1         b=6                       0.1        b=6


                                        0                                   0

    Number of                  -0.1                                       -0.1
    JG groups                               0     2         4    6    8          0     5     10     15   20
                                                                                                              18
                                                        m                                    m
Conclusions


▶   Indirect reciprocity with group-structured
    information sharing yields ingroup favoritism.
▶   Ingroup bias is severer than under JG than under ST.




                                                           19

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Ingroup favoritism under indirect reciprocity

  • 1. Groupwise information sharing promotes ingroup favoritism in indirect reciprocity Mitsuhiro Nakamura & Naoki Masuda Department of Mathematical Informatics The University of Tokyo, Japan M. Nakamura & N. Masuda. BMC Evol Biol 2012, 12:213 http:/www.biomedcentral.com/1471-2148/12/213 1
  • 2. Indirect reciprocity Alexander, Hamilton, Nowak & Sigmund ▶ A mechanism for sustaining cooperation Cost of help Benefit !! "# "# Later, the cost of help is compensated by others’ help 2
  • 3. What stabilizes cooperation in indirect reciprocity? 1. Apposite reputation assignment rules 2. Apposite sharing of reputation information in the population 3
  • 4. Reputation assignment rules Image scoring (IM) Donor’s action: Recipient’s cooperation (C) G B reputation: or defection (D) good (G) or bad (B) C G G D B B ▶ C is good and D is bad ▶ Not ESS (Leimar & Hammerstein, Proc R Soc B 2001) 4
  • 5. Reputation assignment rules Simple standing (ST) Stern judging (JG) G B G B C toward a B player is B! C G G C G B D B G D B G D against a B D against a B player is G player is G ▶ ESS (e.g., Ohtsuki & Iwasa, JTB 2004) 5
  • 6. What stabilizes cooperation in indirect reciprocity? 1. Apposite reputation assignment rules 2. Apposite sharing of reputation information in the population Incomplete Group structure information sharing (not well-mixed) ignored ignored ▶ We assumed groupwise information sharing and (unexpectedly) found the emergence of ingroup favoritism in indirect reciprocity 6
  • 7. Ingroup favoritism Tajfel et al., 1971 ▶ Humans help members in the same group (ingroup) more often than those in the other group (outgroup). ▶ Connection between ingroup favoritism and indirect reciprocity has been suggested by social psychologists (Mifune, Hashimoto & Yamagishi, Evol Hum Behav 2010) 7
  • 8. Explanations for ingroup favoritism ▶ Green-beard effect (e.g., Jansen & van Baalen, Nature 2006) ▶ Tag mutation and limited dispersal (Fu et al., Sci Rep 2012) ▶ Gene-culture co-evolution (Ihara, Proc R Soc B 2007) ▶ Intergroup conflict (e.g., Choi & Bowles, Science 2007) ▶ Disease aversion (Faulkner et al., Group Proc Int Rel 2004) ▶ Direct reciprocity (Cosmides & Toobey, Ethol Sociobiol 1989) ▶ Indirect Reciprocity (Yamagishi et al., Adv Group Proc 1999) 8
  • 9. Model ▶ Donation game in a group- structured population (ingroup game occurs with prob. θ) "$ ▶ Observers in each group assign reputations to players based on a common !! "# assignment rule "# "# ▶ Observers assign wrong reputations with prob. µ << 1 9
  • 10. Reputation dynamics d M () = − () + θ ( ) + (1 − θ)− ( ) Φ (σ ( ) ) d ∈{GB}M =1 ▶ where, r=(G,G,B) () Prob. that a player in group k has reputation vector r in the eyes of M observers Group 3 − () ≡ ()/(M − 1) $ Group 1 Group 2 = !! # σ () Donor’s action: σ (G) = C σ (B) = D # # Φ ( ) Prob. that an observer assigns r when the observer scalar observes action a toward recipient with reputation r’ 10
  • 11. Ingroup reputation dynamics d M () = − () + θ ( ) + (1 − θ)− ( ) Φ (σ ( ) ) d ∈{GB}M =1 d in () = −in () + θin ( ) + (1 − θ)out ( ) Φ (σ ( ) ) d ∈{GB} 11
  • 12. Outgroup reputation dynamics d M () = − () + θ ( ) + (1 − θ)− ( ) Φ (σ ( ) ) d ∈{GB}M =1 d out () = −out () + d ∈{GB} ∈{GB} 1 1 θin ( )out ( ) + (1 − θ) out ( )in ( ) + 1 − out ( )out ( ) Φ (σ ( ) ) M −1 M −1 12
  • 13. Results: Cooperativeness and ingroup bias Frac. G Frac. G Ingroup (ingroup) (outgroup) Prob. C bias Rule ∗ (G) in ∗ (G) out ψ ρ 1 1 1 IM 2 2 2 0 1+θ µ µ ST 1−µ 1−µ 1− θ θ θ 1 1+θ 1 JG 1−µ − µθ −µ 2 2 2 ψ ≡ θ∗ (G) + (1 − θ)∗ (G) in out ρ ≡ ∗ (G) − ∗ (G) in out 13
  • 14. Results: Individual-based simulations (a) 1 IM ST ψ ST, theory 1.0 1.0 0.5 ST, M = 2 ST, M = 10 0.8 0.8 Player Prob. C JG, theory 0.6 0.6 JG, M = 2 0.4 0.4 0 JG, M = 10 0.2 0.2 0 0.5 1 JG 0.0 0.0 Group −0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 −0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 θ (b) 1.0 0.5 0.8 G 0.6 B ρ 0.4 0.25 Ingroup bias 0.2 0.0 −0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 N=300, µ=.01, N=103, µ=.01 0 M=3, θ=.6 0 0.5 1 14 θ
  • 15. Results: Cases with error in actions (a) 1 ψ ▶ Donors fail in cooperation 0.5 ST, theory ST, = 0.01 with prob. ε Prob. C ST, = 0.1 JG, theory JG, = 0.01 0 JG, = 0.1 0 0.5 1 θ (b) 0.5 ρ 0.25 Ingroup bias N=103, µ=.01, M=10 0 0 0.5 1 15 θ
  • 16. Results: Evolutionary stability ▶ Conditions under which players using reputations are stable against invasion by unconditional cooperators and defectors: ST 1 public reputation: θ = 1 1 1−θ private reputation: θ → 1/M, M → ∞ JG (M−1)(1+θ) M−1 1 1+(M−3)θ+Mθ 2 1−Mθ if 0 ≤ θ M (M−1)(1+θ) 1+(M−3)θ+Mθ 2 if 1 M ≤θ≤1 1 → (M → ∞) θ 16
  • 17. Results: Mixed assignment rules ▶ Observers use JG with prob. α and ST with prob. 1-α a b c 1 0.5 5 M2 Θ 0.6 Ψ Ρ 4 bc 0.5 0.25 3 M 2, Θ 0.6 M , Θ 0.6 M 2, Θ 0.2 2 M , Θ 0.2 0 0 1 0 0.5 1 0 0.5 1 0 0.5 1 ST Α JG ST Α JG ST Α JG d e f 5 5 5 M M2 M Θ 0.6 Θ 0.2 Θ 0.2 4 4 4 bc bc bc 3 3 3 2 2 2 1 1 1 0 0.5 1 0 0.5 1 0 0.5 1 ST Α JG ST Α JG ST Α JG 17
  • 18. Results: Heterogeneous assignment rules ▶ Different groups use different rules (either ST or JG) (a) (b) 1 1 ψST , ψJG , ρST , ρJG ψST ρST ψST ρST ψJG ρJG ψJG ρJG 0.5 0.5 0 0 0 2 4 6 8 0 5 10 15 20 (c) (d) 0.2 M=8 0.2 M=20 b=2 b=2 b=4 b=4 πJG − πST 0.1 b=6 0.1 b=6 0 0 Number of -0.1 -0.1 JG groups 0 2 4 6 8 0 5 10 15 20 18 m m
  • 19. Conclusions ▶ Indirect reciprocity with group-structured information sharing yields ingroup favoritism. ▶ Ingroup bias is severer than under JG than under ST. 19