* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Collective Action Behavior and Social Institutions
Gene therapy wikipedia , lookup
Gene desert wikipedia , lookup
Therapeutic gene modulation wikipedia , lookup
Site-specific recombinase technology wikipedia , lookup
Gene nomenclature wikipedia , lookup
Population genetics wikipedia , lookup
Artificial gene synthesis wikipedia , lookup
Designer baby wikipedia , lookup
Institutions and the Evolution of Collective Action Mark Lubell UC Davis Defining Collective Action Collective-action problem: Individual decision-making leads to socially undesirable (Pareto-inefficient) outcomes Cooperation: Adjusting behavior to minimize socially undesirable outcomes Tragedy of the Commons Garrett Hardin (1968): “Therein is the tragedy. Each man is locked into a system that compels him to increase his herd without limit—in a world that is limited. Ruin is the destination towards which all men rush, each his own best interest in a society that believes in freedom of the commons.” “Mutual coercion, mutually agreed upon” Flip side of resource use: Maintenance of ecosystems/public goods Collective action problems are ubiquitous! From Global…. To Local… To Local… Studying Collective Action Major Research Questions 1. Factors explaining cooperative behavior 2. Role of institutions (e.g., punish defection, reward cooperation) Theoretical Philosophy Game theory Evolutionary game theory Evolutionary simulations (This talk) Empirical Field research (qualitative and quantitative) Experimental research Prisoner’s Dilemma Player 2 Cooperate Defect Cooperate R1= 6 R2= 6 S1 = 3 T2= 8 Defect T1= 8 S2= 3 P1 = 4 P2 = 4 Player 1 Conditions: T>R>P>S; 2R>T+S Nash equilibrium: Both players defect Collective Action Agents Five “gene” strategies; 32 possible Each gene determines behavior in current round on basis of outcome in last round <Nice (1st round), Reciprocal (CC), Sucker(CD), Forgive (DC), Protect (DD)> Important Examples: All Cooperate <1,1,1,1,1> GRIM Trigger <1,1,0,0,0> PAVLOV(Win-stay, lose shift) <1,1,0,0,1> Tit-for-Tat <1,1,0,1,0> Structure of Simulation Generation 1: Randomly Select 40 Strategies Round Robin Tournament: Each strategy vs. itself and all others Next Generation: Survival of Fittest 1% Mutation Rate on Each Gene Generation 1 Proportional Fitness Reproduction: P(reproduction)= Fitnessi/Fitnessall Generation 5000 A “Punishing” Experiment Design Baseline 2-player repeated PD, with discount rate= .9 Examine the effect of $2 punishment for defection, with increasing probability ranging from [0,1] in .10 increments 10 runs of each experiment; 40 strategies, 5000 generations Hypotheses Increasing levels of cooperation Increased population stability Shift in the population dynamics of cooperation 4914 4625 4336 4047 3758 3469 3180 2891 2602 2313 2024 1735 1446 1157 868 579 290 1 7 6 5 4 3 Mean Fitness 2 1 0 45 40 35 30 25 20 grim pavlov 15 10 5 0 4999 4705 4411 4117 3823 3529 3235 2941 2647 2353 2059 1765 1471 1177 883 589 295 1 Hobbes: Punishment p=1.0 7 6 5 4 3 Mean Fitness 2 1 0 45 40 35 30 25 20 grim pavlov 15 10 5 0 Mean Fitness Increases With Punishment Probability 5.8 5.6 Mean Fitness 5.4 5.2 Generation Mean Fitness 5 4.8 4.6 4.4 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Punishment Probability 1 Gene Frequency: All Regimes Nice CC CD DC DD Average Gene Frequency Per Generation 40 35 30 25 20 15 10 5 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Punishment Probability 0.8 0.9 1 Strategy Frequency: All Regimes 14 Average Strategy Frequency 12 10 8 GRIM PAVLOV SPAVLOV 6 4 2 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Punishment Probability 0.8 0.9 1 Gene Frequency: Cooperative Regimes (Avg. Fitness>5.9) Nice CC CD DC DD 45 40 Gene Frequency 35 30 25 20 15 10 5 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Punishment Probability 0.8 0.9 1 Strategy Frequency: Cooperative Regimes 34 Average Strategy Frequency 29 24 GRIM PAVLOV SPAVLOV TFT 19 14 9 4 -1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Punishment Probability 0.8 0.9 1 Some Correlations Overall Fitness .21 Genes Nice .11 CC .22 CD .10 DC .06 DD .24 Strategies All Defect -.18 GRIM -.03 PAVLOV .10 Suspicious PAVLOV .10 TFT .04 Conclusions Punishment institutions increase cooperation and stability, even in noisy environment As punishment increase, basis of cooperation shifts towards PAVLOV Institutions change population dynamics of cooperation, even if same behaviors observed Must square with observed human behavior; e.g.; resistance to coercion, reduced effectiveness of reciprocity in coercive environments