Evolution of cooperation driven by collective interdependence on multilayer networks

Chen, Wei; Yang, Zhihu; Wu, Te

doi:10.1016/j.amc.2020.125532

Cited by 8 publications

(5 citation statements)

References 45 publications

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“…A recent work reveals that the combination of external political campaigns (or mass medias) and online social influence processes could give rise to partisan echo chambers [14]. Complicating matters further, the complex interplay between different social networks could also affect cognition diffusion [15,16], leading to the emergence of rich and important physical phenomena such as non-monotonic promotion [17], phase transition [18], and bistability [19], which has been demonstrated by numerous studies using multiplex networks [20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Co-evolutionary Game Dynamics of Competitive Cognitions and Public Opinion Environment

et al. 2021

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Competitive cognition dynamics are widespread in modern society, especially with the rise of information-technology ecosystem. While previous works mainly focus on internal interactions among individuals, the impacts of the external public opinion environment remain unknown. Here, we propose a heuristic model based on co-evolutionary game theory to study the feedback-evolving dynamics of competitive cognitions and the environment. First, we show co-evolutionary trajectories of strategy-environment system under all possible circumstances. Of particular interest, we unveil the detailed dynamical patterns under the existence of an interior saddle point. In this situation, two stable states coexist in the system and both cognitions have a chance to win. We highlight the emergence of bifurcation phenomena, indicating that the final evolutionary outcome is sensitive to initial conditions. Further, the attraction basins of two stable states are not only influenced by the position of the interior saddle point but also affected by the relative speed of environmental feedbacks.

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Section: Introductionmentioning

confidence: 99%

Co-evolutionary Game Dynamics of Competitive Cognitions and Public Opinion Environment

et al. 2021

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“…While gametheoretical decision making on multiplex and multilayer networks has also been studied in some prior works [7], [23]- [27], the majority of the research has focused on evolutionary games and the emergence of cooperation in public good games. In particular, the emergence and sustainability of cooperation strategies in public good games has been explored in multiplex networks by [24], [25] and in multilayer networks by [26], [27]. Despite considering games on multilayer/multiplex networks and identifying what network structures can enhance the resilience of cooperation, these prior works have considered a binary action (cooperate/defect) game, and often restrict focus to specific classes of graphs.…”

Section: A Related Literaturementioning

confidence: 99%

United We Fall: On the Nash Equilibria of Multiplex Network Games

Ebrahimi,

Naghizadeh

2023

2023 59th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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Network games provide a framework to study strategic decision making processes that are governed by structured interdependencies among agents. However, existing models do not account for environments in which agents simultaneously interact over multiple networks, or when agents operate over multiple action dimensions. In this paper, we propose new models of multiplex network games to capture the different modalities of interactions among strategic agents, and multilayer network games to capture their interactions over multiple action dimensions. We explore how the properties of the constituent networks of a multiplex/multilayer network can undermine or support the existence, uniqueness, and stability of the game's Nash equilibria. Notably, we highlight that both the largest and smallest eigenvalues of the constituent networks (reflecting their connectivity and two-sidedness, respectively) are instrumental in determining the uniqueness of the multiplex/multilayer network game's equilibrium. Together, our findings shed light on the reasons for the fragility of equilibria when agents interact over networks of networks, and point out potential interventions to alleviate them.

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“…Consequently, the final outcome, specifically the cooperation density, becomes independent of the payoff parameters. In another study, Chen explored the evolution of cooperation driven by collective interdependence on multilayer networks 23 . Theses researches highlighted the significant impact of collective interdependence on interdependent network reciprocity.…”

Section: Introductionmentioning

confidence: 99%

Impact of Discrepant Accumulations Strategy on Collective Cooperation in Multilayer Networks

He,

Ge,

Yang

et al. 2024

Preprint

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Understanding large-scale cooperation among related individuals has been one of the largest challenges. Since humans are in multiple social networks, the theoretical framework of multilayer networks is perfectly suited for studying this fascinating aspect of our biology. To that effect, we here study the cooperation in evolutionary game on interdependent networks. Importantly, a part of players are set to adopt Discrepant Accumulations Strategy. Players employing this mechanism not only use their payoffs in the multilayer network as the basis for the updating process as in previous experiments, but also take into account the similarities and differences in strategies across different layers. Monte Carlo simulations demonstrate that considering the similarities and differences in strategies across layers when calculating fitness can significantly enhance the cooperation level in the system. By examining the behavior of different pairing mode within cooperators and defectors, the equilibrium state can be attributed to the evolution of correlated pairing mode between interdependent networks. Our results provide a theoretical analysis of the group cooperation induced by the Discrepant Accumulations Strategy. And we also discuss potential implications of these findings for future human experiments concerning the cooperation on multilayer networks.

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Evolution of cooperation driven by collective interdependence on multilayer networks

Cited by 8 publications

References 45 publications

Co-evolutionary Game Dynamics of Competitive Cognitions and Public Opinion Environment

Co-evolutionary Game Dynamics of Competitive Cognitions and Public Opinion Environment

United We Fall: On the Nash Equilibria of Multiplex Network Games

Impact of Discrepant Accumulations Strategy on Collective Cooperation in Multilayer Networks

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