由外向性、开放性和宜人性驱动的动态网络囚徒困境中合作与互惠的个体和集体收益
Individual and collective gains from cooperation and reciprocity in a dynamic-network Prisoner's Dilemma driven by extraversion, openness, and agreeableness
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中文总结 AI 辅助
研究社会关系可形成和解散时人格差异对合作的影响，通过在内生网络模拟重复囚徒困境，结合大五人格特质与伙伴历史，改变网络规模等因素，发现先合作后互惠更优，人格有条件效应，网络会相应重组。
中文摘要 AI 辅助
当社会关系可以形成和解散时，稳定的人格差异如何塑造合作？我们在内生网络上模拟重复囚徒困境，其中三种连续的大五人格特质映射到透明的局部机制：外向性设定伙伴目标数量，开放性决定行动者在朋友的朋友之外搜索的广度，宜人性设定合作的基线意愿。每次相遇时，行动者将此基线与伙伴直接观察到的历史相结合；不存在特质标签、流言蜚语或全局声誉。当行动者联系不足时形成联系，联系过多时切断联系，切断联系时优先考虑叛逃更频繁的伙伴。我们改变网络规模（N = 30 - 200）、群体组成以及特质驱动和历史驱动行为之间的平衡。出现了三种稳健模式。首先，先合作然后互惠——高初始合作意愿与历史敏感反应相结合——产生同时更繁荣、更公平和更安全的系统。其次，人格有可预测的条件效应：当历史重要时宜人性有帮助，但当行为主要由特质驱动时有害；外向性放大环境；开放性几乎没有净收益效应。第三，网络相应地重新组织：度 assortativity 保持接近零，而当合作确立时，宜人的行动者越来越多地相互连接。
英文摘要
How do stable personality differences shape cooperation when social ties can form and dissolve? We model a repeated Prisoner's Dilemma on an endogenous network in which three continuous Big Five traits map to transparent local mechanisms: Extraversion sets a target number of partners, Openness determines how broadly agents search beyond friends-of-friends, and Agreeableness sets a baseline willingness to cooperate. At each encounter, agents combine this baseline with the partner's directly observed history; there are no trait labels, gossip, or global reputations. Ties form when agents are under-connected and are cut when they become over-connected, with cuts prioritising partners who have defected more often. We vary network size (N=30--200), population composition, and the balance between trait-driven and history-driven behaviour. Three robust patterns emerge. First, cooperate first, then reciprocate---high initial willingness to cooperate combined with history-sensitive response---produces systems that are simultaneously more prosperous, fairer, and safer. Second, personality has predictable conditional effects: Agreeableness helps when history matters but hurts when behaviour is mostly trait-driven; Extraversion amplifies the environment; Openness has little net payoff effect. Third, the network reorganises accordingly: degree assortativity stays near zero, whereas agreeable agents increasingly connect to one another when cooperation takes hold.
