The Evolution of Cooperation In N-Person Public
Goods Game
Under Different Social Enviornments
Jung-Kyoo Choi
jungk@econs.umass.edu
We analyze the evolution of cooperation in N-person social
dilemmas. Agents are assigned into groups and play a repeated N-person public
goods game. Games are played under different settings. Agents either interact
with a random group (global) or the same group (local). Furthermore agents
either update their strategies based on global scale or on their neighbors’
strategies. Therefore we have four different combinations, each of which
is an analogy of different social environment.
Global Interaction Local Interaction
Global Selection Market Long-term
Relationship(e.g. firms)
Local Selection Peer Group Updating
Segregated Small Village
A genetic algorithm is used to adapt the strategies with a
selection mechanism that involves either global or local agents. With
random groupings, defection is the norm with some occasional, short-lived
outbreaks of cooperation. These outbreaks are enhanced when selection is
local. When agents stay within the same group cooperative outcomes are much
more likely, with relatively high levels of sustained cooperation in many
of the resulting groups when selection is global. This effect disappears
when the selection is local.
Localizing agents’ interactions is a way to sustain cooperation
by generating group benefit, whereas group benefit is only transitory in
random grouping. However this benefit can be sustained only when local interaction
is paired with global selection. We found that “group selection process”
plays an important role in this dynamics. Localized interactions and global
selection allow group selection process to come to exist.
We also found that genetic drift occurs in strategy (gene)
space and plays a crucial role. It greatly enlarges the effect of mutation
and helps cooperative strategy spreading over the population (even if it
is dominated strategy). The role of genetic drift is discussed in detail
in this paper.