Nonlinear Sciences – Adaptation and Self-Organizing Systems
Scientific paper
2002-11-15
Physica A326 (2003) 286-298
Nonlinear Sciences
Adaptation and Self-Organizing Systems
11 pages, 5 figures
Scientific paper
10.1016/S0378-4371(03)00263-2
The self-organization in cooperative regimes in a simple mean-field version of a model based on "selfish" agents which play the Prisoner's Dilemma (PD) game is studied. The agents have no memory and use strategies not based on direct reciprocity nor 'tags'. Two variables are assigned to each agent $i$ at time $t$, measuring its capital $C(i;t)$ and its probability of cooperation $p(i;t)$. At each time step $t$ a pair of agents interact by playing the PD game. These 2 agents update their probability of cooperation $p(i)$ as follows: they compare the profits they made in this interaction $\delta C(i;t)$ with an estimator $\epsilon(i;t)$ and, if $\delta C(i;t) \ge \epsilon(i;t)$, agent $i$ increases its $p(i;t)$ while if $\delta C(i;t) < \epsilon(i;t)$ the agent decreases $p(i;t)$. The 4!=24 different cases produced by permuting the four Prisoner's Dilemma canonical payoffs 3, 0, 1, and 5 - corresponding,respectively, to $R$ (reward), $S$ (sucker's payoff), $T$ (temptation to defect) and $P$ (punishment) - are analyzed. It turns out that for all these 24 possibilities, after a transient,the system self-organizes into a stationary state with average equilibrium probability of cooperation $\bar{p}_\infty$ = constant $ > 0$.Depending on the payoff matrix, there are different equilibrium states characterized by their average probability of cooperation and average equilibrium per-capita-income ($\bar{p}_\infty,\bar{\delta C}_\infty$).
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