Li Aming, Wu Bin, Wang Long
Center for Systems and Control, State Key Laboratory for Turbulence and Complex Systems, College of Engineering, Peking University, 100871 Beijing, China.
Department of Evolutionary Theory, Max-Planck-Institute for Evolutionary Biology, August-Thienemann-Str. 2, 24306 Plön, Germany.
Sci Rep. 2014 Jul 2;4:5536. doi: 10.1038/srep05536.
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.
从多细胞生物到人类社会,合作无处不在。表明个体有限互动范围的种群结构对于理解这一问题至关重要。但尚不清楚涉及收益非线性的多重互动在何种程度上会影响结构化种群中的合作。在此,我们展示了一条规则,该规则决定了在多重贴现、线性和协同互动下合作的出现与稳定。该规则通过在同质和异质结构化种群中的模拟得到验证。我们发现,对于具有线性和贴现的多重互动而言,邻居越多,合作就越难演化。然而,对于协同情景,与两两互动的情况不同,适度数量的邻居可能是最不利的,这表明协同互动与陌生人合作有效,但与邻居则不然。我们的结果表明,单独促进合作的不同因素的组合可能比每个单一因素的情况更糟。