部分利用者维持合作：驼峰策略稳定共存于无条件合作者
Partial exploiters sustain cooperation: the hump-shaped strategy stably coexists with unconditional cooperators
AI总结：
研究揭示驼峰策略在中间规模群体中适应性强，能与无条件合作者共同维持大规模合作，通过稳定均衡排除自由搭车者。
摘要：
从集体狩猎到环境问题，社会困境在人类社会中普遍存在。先前研究已记录了此类情境中高度异质的行为模式。然而，这种异质性如何产生以及如何塑造大规模合作仍不清楚。本文聚焦于一个稳健观察但研究不足的模式：驼峰策略（Hump）。采用者根据阈值匹配他人的贡献，超过阈值则减少自身贡献。通过不同群体规模和生产函数形状的 agent-based 模拟，发现驼峰策略在中间规模群体中尤其适应性强。尽管其剥削性，驼峰策略也能提升群体合作水平。其机制是驼峰策略能与无条件合作者（AllC）形成稳定均衡，共同在广泛环境中排除自由搭车者。研究发现，未被充分探索的行为异质性模式——包括驼峰和 AllC——在维持大规模合作中发挥功能作用。
英文摘要：
From collective hunting to environmental problems, social dilemmas are pervasive in human societies. Prior research has documented highly heterogeneous behavioral patterns in such settings. However, how this heterogeneity emerges and how it shapes large-scale cooperation remain unclear. Here, we focus on a robustly observed but underexplored pattern: the hump-shaped strategy (Hump). Individuals adopting Hump match others' contributions up to a threshold, only to reduce their own above it. Using agent-based simulations across group sizes and production-function shapes, we find that Hump is individually adaptive, especially in intermediate-sized groups with step-like production functions. Despite its exploitative nature, Hump also elevates population-level cooperation. The underlying mechanism is that Hump can form a stable equilibrium with unconditional cooperators (AllC), which jointly exclude defectors across a broad range of environments. Our findings suggest that underexplored patterns of behavioral heterogeneity -- including both Hump and AllC -- play a functional role in sustaining large-scale cooperation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
