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Free keywords:
public goods games; evolution of cooperation; learning process;
memory size
Abstract:
We propose an individual-based model to describe the effects of memory and learning in
the evolution of cooperation in a public goods game (PGG) in a well-mixed population. Individuals
are endowed with a set of strategies, and in every round of the game they use
one strategy out of this set based on their memory and learning process. The payoff of a
player using a given strategy depends on the public goods enhancement factor r and the
collective action of all players. We investigate the distribution of used strategies as well
as the distribution of information patterns. The outcome depends on the learning process,
which can be dynamic or static. In the dynamic learning process, the players can switch
their strategies along the whole game, and use the strategy providing the highest payoff at
current time step. In the static learning process, there is a training period where the players
randomly explore different strategies out of their strategy sets. In the rest of the game,
players only use the strategy providing the highest payoff during the training period. In
the dynamic learning process, we observe a transition from a non-cooperative regime to a
regime where the level of cooperation reaches about 50%. As in the standard PGG, in the
static learning process there is a transition from the non-cooperative regime to a regime
where the level of cooperation can be higher than 50% at r = N. In both learning processes
the transition becomes smoother as the memory size of individuals increases, which means
that the lack of information is a key ingredient causing the defection.