Inequal dependence on members stabilizes cooperation in spatial public goods game

Yu, Fengyuan; Wang, Jianwei; He, Jialu

doi:10.1016/j.chaos.2022.112755

Cited by 13 publications

(2 citation statements)

References 83 publications

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“…In the spatial public goods game framework [43][44][45][46][47][48], we consider a square lattice of size L × L and population N = L 2 , where each agent i occupies a node and forms a group Ω i with size G = 5, consisting of itself and its four nearest neighbors. Consequently, agent i is also a member of the groups Ω j of its neighbors j ∈ Ω i \ {i}.…”

Section: Modelmentioning

confidence: 99%

Competition between self- and other-regarding preferences in resolving social dilemmas

Wang,

Szolnoki

2024

New J. Phys.

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Evolutionary game theory assumes that individuals maximize their benefits when choosing strategies. However, an alternative perspective proposes that individuals seek to maximize the benefits of others. To explore the relationship between these perspectives, we develop a model where self- and other-regarding preferences compete in public goods games. We find that other-regarding preferences are more effective in promoting cooperation, even when self-regarding preferences are more productive. Cooperators with different preferences can coexist in a new phase where two classic solutions invade each other, resulting in a dynamical equilibrium. As a consequence, a lower productivity of self-regarding cooperation can provide a higher cooperation level. Our results, which are also valid in a well-mixed population, may explain why other-regarding preferences could be a viable and frequently observed attitude in human society.

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Section: Modelmentioning

confidence: 99%

Competition between self- and other-regarding preferences in resolving social dilemmas

Wang,

Szolnoki

2024

New J. Phys.

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“…This is the key element which establishes the so-called network reciprocity, first identified by Nowak and May [1]. This mechanism, which is practically an enhanced form of direct reciprocity [2], has been tested and justified by several forthcoming works [3,4,5,6,7,8] and became a starting element when different consequences of interaction topologies were studied on the evolution of cooperation [9,10,11,12]. Notably, there are certain mechanisms, like searching for a more supportive environment [13,14], avoiding toxic neighbors via migration [15,16], giving up the concept of uniform supporting and focusing on a specific neighbor [17,18,19,20], or applying interaction stochasticity toward different neighbors [21,22], which cannot be interpreted in a well-mixed population.…”

Section: Introductionmentioning

confidence: 95%