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Free keywords:
applied mathematics; evolutionary theory; social evolution
Abstract:
Cooperation is ubiquitous ranging from multicellular organisms to human societies. Population structures
indicating individuals’ limited interaction ranges are crucial to understand this issue. But it remains
unknown to what extend multiple interactions involving nonlinearity in payoff influence the cooperation in
structured populations. Here we show a rule, which determines the emergence and stabilization of
cooperation, under multiple discounted, linear, and synergistic interactions. The rule is validated by
simulations in homogenous and heterogenous structured populations. We find that the more neighbours
there are the harder for cooperation to evolve for multiple interactions with linearity and discounting. For
synergistic scenario, however, distinct from its pairwise counterpart, moderate number of neighbours can
be the worst, indicating that synergistic interactions work with strangers but not with neighbours. Our
results suggest that the combination of different factors which promotes cooperation alone can be worse
than that with every single factor.
