Department of Physics, Cornell University, 142 Sciences Drive, Ithaca, NY 14853, USA
ASU-SFI Center for Biosocial Complex Systems, Arizona State University, Tempe, AZ 85287, USA.
J R Soc Interface. 2017 Sep;14(134). doi: 10.1098/rsif.2017.0223.
In biological systems, prolonged conflict is costly, whereas contained conflict permits strategic innovation and refinement. Causes of variation in conflict size and duration are not well understood. We use a well-studied primate society model system to study how conflicts grow. We find conflict duration is a 'first to fight' growth process that scales superlinearly, with the number of possible pairwise interactions. This is in contrast with a 'first to fail' process that characterizes peaceful durations. Rescaling conflict distributions reveals a universal curve, showing that the typical time scale of correlated interactions exceeds nearly all individual fights. This temporal correlation implies collective memory across pairwise interactions beyond those assumed in standard models of contagion growth or iterated evolutionary games. By accounting for memory, we make quantitative predictions for interventions that mitigate or enhance the spread of conflict. Managing conflict involves balancing the efficient use of limited resources with an intervention strategy that allows for conflict while keeping it contained and controlled.
在生物系统中，长期冲突代价高昂，而有节制的冲突则允许战略创新和改进。导致冲突规模和持续时间变化的原因尚不清楚。我们使用一个经过充分研究的灵长类动物社会模型系统来研究冲突是如何发展的。我们发现，冲突的持续时间是一种“先战”的增长过程，与可能的成对相互作用的数量呈超线性比例。这与和平持续时间所描述的“先失败”过程形成对比。对冲突分布进行重新缩放揭示了一条普遍的曲线，表明相关相互作用的典型时间尺度超过了几乎所有的个体战斗。这种时间相关性意味着在标准的传染增长模型或迭代进化博弈中所假设的那些之外，在成对相互作用中存在集体记忆。通过考虑记忆，我们对减轻或增强冲突传播的干预措施做出了定量预测。管理冲突需要平衡有限资源的有效利用与干预策略，该策略既要允许冲突，又要将其控制在一定范围内。
