Topological enslavement in evolutionary games on correlated multiplex networks

Abstract

Governments and enterprises strongly rely on incentives to generate favorable outcomes from social and strategic interactions between individuals. The incentives are usually modeled by payoffs in evolutionary games, such as the prisoners dilemma or the harmony game, with imitation dynamics. Adjusting the incentives by changing the payoff parameters can favor cooperation, as found in the harmony game, over defection, which prevails in the prisoner's dilemma. Here, we show that this is not always the case if individuals engage in strategic interactions in multiple domains. In particular, we investigate evolutionary games on multiplex networks where individuals obtain an aggregate payoff. We explicitly control the strength of degree correlations between nodes in the different layers of the multiplex. We find that if the multiplex is composed of many layers and degree correlations are strong, the topology of the system enslaves the dynamics and the final outcome, cooperation or defection, becomes independent of the payoff parameters. The fate of the system is then determined by the initial conditions. OPEN ACCESS RECEIVED

Strategic Differentiation in Non-Cooperative Games on Networks

“…Indeed, whe observed that when there are many differentiators in the network the influence of the benefit to cost ratio r on the total contributions in equilibrium is suppressed. This effect is similar to topological enslavement [11] seen in evolutionary games on multiplex networks in which hubs dominate the game dynamics. When the differentiators are placed on low degree nodes, these effects are mitigated.…”

“…One such mechanism is known as network reciprocity: when a cooperator pays some cost that its neighbors can benefit from and a defector bears no costs, not creating any benefit for its neighbors, then cooperators can succeed by forming clusters in the network [8]. Evolutionary games on networks and the study of their evolutionary success have later been generalized to include groupwise interactions [9], and multilayer networks [10], [11]. An extensive review of these games can be found in [12].…”

Link persistence and conditional distances in multiplex networks

“…tection and trans-layer link prediction on a geometric basis, as well as multilayer greedy routing [14]. Furthermore, it was shown that the discovered correlations play an important role in the robustness of multiplexes against targeted attacks to high degree nodes [31] and to the outcome of evolutionary dynamics [32,33]. Yet, despite these advances, it is still not fully understood to what extend can coordinate correlations alone explain the topological relation between the layers of real systems.…”

Evolution of cooperation in synergistically evolving dynamic interdependent networks: fundamental advantages of coordinated network evolution

“…In line with the previous study [26], we use the mean payoff that i collects in all layers to quantify iʼs effective payoff Π i that ultimately maps into strategy dynamics, i.e. i…”

“…Myriad mechanisms such as kin selection [5,6], punishment [7][8][9][10] and voluntary participation [11] are proposed to rescue such cooperation tragedy in this spectrum (see review [12,13]). In particular, by taking into account the following aspects, the recent shift from evolutionary games in well-mixed populations [14][15][16] and static networks [17][18][19][20][21][22][23] to evolutionary games in multiplex networks [24][25][26][27] and dynamic networks [28][29][30][31][32][33][34] has stimulated mounting efforts in exploring cooperation dynamics in more realistic scenarios (see review [35][36][37][38]).…”