催化合作:结构化人群中集体信念的力量

Małgorzata Fic, Chaitanya S. Gokhale
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摘要

集体信念可以促进自私个体之间的合作。我们研究了集体信念的这种变革力量,即使在信念缺乏道德成分的情况下,这种效应依然存在,令人好奇。除了过程本身,我们还明确考虑了人类种群的结构。我们将人类群体错综复杂的结构纳入我们的模型,承认社会和文化身份在互动网络中带来的偏差。因此,我们在建立模型时假定了群体规模和群体结构的异质性。我们认识到,信仰作为典型的复杂故事系统,可能不会在社会中自发出现,从而导致行动和信仰在人群中的传播率不同。由于延续信念的个体之间的联系程度可能不同,我们研究了在具有不同联系密度的网络中建立信任的速度。然后,我们仔细研究了特定网络结构中信任和信念传播的时间、速度和动态,包括随机埃尔德斯-雷尼网络、无标度巴拉巴西-阿尔伯特网络和小世界纽曼-瓦茨-斯特罗加茨网络。通过比较不同网络拓扑结构的这些特征,我们厘清了结构、群体规模多样性和进化动力学对信任和信念进化的影响。
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Catalysing cooperation: the power of collective beliefs in structured populations
Collective beliefs can catalyse cooperation in a population of selfish individuals. We study this transformative power of collective beliefs, an effect that intriguingly persists even when beliefs lack moralising components. Besides the process itself, we consider the structure of human populations explicitly. We incorporate the intricate structure of human populations into our model, acknowledging the bias brought by social and cultural identities in interaction networks. Hence, we develop our model by assuming a heterogeneous group size and structured population. We recognise that beliefs, typically complex story systems, might not spontaneously emerge in society, resulting in different spreading rates for actions and beliefs within populations. As the degree of connectedness can vary among individuals perpetuating a belief, we examine the speed of trust build-up in networks with different connection densities. We then scrutinise the timing, speed and dynamics of trust and belief spread across specific network structures, including random Erdös-Rényi networks, scale-free Barabási-Albert networks, and small-world Newman-Watts-Strogatz networks. By comparing these characteristics across various network topologies, we disentangle the effects of structure, group size diversity, and evolutionary dynamics on the evolution of trust and belief.
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