Su Qi, McAvoy Alex, Plotkin Joshua B
Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA.
Center for Mathematical Biology, University of Pennsylvania, Philadelphia, PA 19104, USA.
Sci Adv. 2022 Feb 11;8(6):eabm6066. doi: 10.1126/sciadv.abm6066. Epub 2022 Feb 9.
How do networks of social interaction govern the emergence and stability of prosocial behavior? Theoretical studies of this question typically assume unconditional behavior, meaning that an individual either cooperates with all opponents or defects against all opponents-an assumption that produces a pessimistic outlook for the evolution of cooperation, especially in highly connected populations. Although these models may be appropriate for simple organisms, humans have sophisticated cognitive abilities that allow them to distinguish between opponents and social contexts, so they can condition their behavior on the identity of opponents. Here, we study the evolution of cooperation when behavior is conditioned by social context, but behaviors can spill over between contexts. Our mathematical analysis shows that contextualized behavior rescues cooperation across a broad range of population structures, even when the number of social contexts is small. Increasing the number of social contexts further promotes cooperation by orders of magnitude.
社会互动网络如何支配亲社会行为的出现与稳定？对这个问题的理论研究通常假定行为是无条件的，也就是说个体要么与所有对手合作，要么与所有对手对抗——这一假设对合作的进化产生了悲观的看法，尤其是在高度连接的群体中。尽管这些模型可能适用于简单生物体，但人类具有复杂的认知能力，使他们能够区分对手和社会情境，因此他们可以根据对手的身份来调整自己的行为。在这里，我们研究当行为受社会情境制约且行为可在不同情境间蔓延时合作的进化。我们的数学分析表明，即使社会情境数量很少，情境化行为也能在广泛的群体结构中挽救合作。增加社会情境的数量会进一步大幅促进合作。
