Basak Amit, Sengupta Supratim
Department of Physical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur Campus, West Bengal, India.
PLoS Comput Biol. 2024 Dec 19;20(12):e1012678. doi: 10.1371/journal.pcbi.1012678. eCollection 2024 Dec.
Humans navigate diverse social relationships and concurrently interact across multiple social contexts. An individual's behavior in one context can influence behavior in other contexts. Different payoffs associated with interactions in the different domains have motivated recent studies of the evolution of cooperation through the analysis of multichannel games where each individual is simultaneously engaged in multiple repeated games. However, previous investigations have ignored the potential role of network structure in each domain and the effect of playing against distinct interacting partners in different domains. Multiplex networks provide a useful framework to represent social interactions between the same set of agents across different social contexts. We investigate the role of multiplex network structure and strategy linking in multichannel games on the spread of cooperative behavior in all layers of the multiplex. We find that multiplex structure along with strategy linking enhances the cooperation rate in all layers of the multiplex compared to a well-mixed population in Prisoners' Dilemma games, provided the network structure is identical across layers. The effectiveness of strategy linking in enhancing cooperation depends on the degree of similarity of the network structure across the layers and perception errors due to imperfect memory. Higher cooperation rates are achieved when the degree of structural overlap of the different layers is sufficiently large, and the probability of perception error is relatively low. Our work reveals how the social network structure in different layers of a multiplex can affect the spread of cooperation by limiting the ability of individuals to link strategies across different social domains.
人类在多样的社会关系中穿梭,并同时在多个社会环境中进行互动。个体在一种环境中的行为会影响其在其他环境中的行为。不同领域互动所带来的不同收益,促使近期通过分析多通道博弈来研究合作的演变,在多通道博弈中,每个个体同时参与多个重复博弈。然而,先前的研究忽略了每个领域中网络结构的潜在作用,以及在不同领域与不同互动伙伴博弈的影响。多重网络提供了一个有用的框架,用于表示同一组主体在不同社会环境中的社会互动。我们研究多重网络结构和策略关联在多通道博弈中对多重网络所有层级合作行为传播的作用。我们发现,与囚徒困境博弈中完全混合的群体相比,在各层网络结构相同的情况下,多重结构以及策略关联能提高多重网络所有层级的合作率。策略关联在促进合作方面的有效性取决于各层网络结构的相似程度以及由于记忆不完美导致的认知误差。当不同层的结构重叠程度足够大且认知误差概率相对较低时,能实现更高的合作率。我们的研究揭示了多重网络不同层中的社会网络结构如何通过限制个体跨不同社会领域关联策略的能力来影响合作的传播。