Coevolutionary dynamics of aspiration and strategy in spatial repeated public goods games

Wu, Te; Fu, Feng; Wang, Long

doi:10.1088/1367-2630/aac687

Cited by 54 publications

(30 citation statements)

References 57 publications

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“…Our present observations underline that this concept can be extended more generally in a coevolutionary framework [17,[38][39][40][41] where the evolution either select one of the learning methods to prevail or allows coexistence by offering new solutions to emerge. Hopefully our extention can be useful for other kind of microscopic rules, including win-stay lose-shift, myopic, other-regarding preference, Pavlov-rule, or in general for those rules which use a sort of aspiration level for personal decision making [42][43][44][45][46][47][48][49][50][51][52][53][54]. Figure 6.…”

Section: Discussionmentioning

confidence: 99%

Competition and partnership between conformity and payoff-based imitations in social dilemmas

Szolnoki¹,

Chen²

2018

New J. Phys.

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Learning from a partner who collects a higher payoff is a frequently used working hypothesis in evolutionary game theory. One of the alternative dynamical rules is when the focal player prefers to follow the strategy choice of the majority in the local neighborhood, which is often called a conformity-driven strategy update. In this work we assume that both strategy learning methods are present and compete for space within the framework of a coevolutionary model. Our results reveal that the presence of a payoff-driven strategy learning method becomes exclusive for high sucker's payoff and/or high temptation values that represent a snowdrift game dilemma situation. In general, however, the competition of the mentioned strategy learning methods could be useful to enlarge the parameter space where only cooperators prevail. The success of cooperation is based on the enforced coordination of cooperator players which reveals the benefit of the latter strategy. Interestingly, the payoff-based and the conformity-based cooperator players can form an effective alliance against defectors that can also extend the parameter space of full cooperator solution in the stag-hunt game region. Our work highlights that the coevolution of strategies and individual features such as the learning method can provide a novel type of pattern formation mechanism that cannot be observed in a static model, and hence remains hidden in traditional models.

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Section: Discussionmentioning

confidence: 99%

Competition and partnership between conformity and payoff-based imitations in social dilemmas

Szolnoki¹,

Chen²

2018

New J. Phys.

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“…The focal player can be of type A, or B, and encounter a group containing k other players of type A, to receive the pay-off a k or b k . The multi-player game [37][38][39][40][41][42][43][44][45][46][47][48][49] payoff matrix is defined as Table 1.…”

Section: The Research On Multi-player Threshold Public Goods Evolutionary Game Model the Multi-player Evolutionary Game Modelmentioning

confidence: 99%

The characteristics of average abundance function with mutation of multi-player threshold public goods evolutionary game model under redistribution mechanism

Xia

2021

BMC Ecol Evo

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Background In recent years, the average abundance function has attracted much attention as it reflects the degree of cooperation in the population. Then it is significant to analyse how average abundance functions can be increased to promote the proliferation of cooperative behaviour. However, further theoretical analysis for average abundance function with mutation under redistribution mechanism is still lacking. Furthermore, the theoretical basis for the corresponding numerical simulation is not sufficiently understood. Results We have deduced the approximate expressions of average abundance function with mutation under redistribution mechanism on the basis of different levels of selection intensity $$\omega$$ ω (sufficiently small and large enough). In addition, we have analysed the influence of the size of group d, multiplication factor r, cost c, aspiration level $$\alpha$$ α on average abundance function from both quantitative and qualitative aspects. Conclusions (1) The approximate expression will become the linear equation related to selection intensity when $$\omega$$ ω is sufficiently small. (2) On one hand, approximation expression when $$\omega$$ ω is large enough is not available when r is small and m is large. On the other hand, this approximation expression will become more reliable when $$\omega$$ ω is larger. (3) On the basis of the expected payoff function $$\pi \left( \centerdot \right)$$ π ⋅ and function $$h(i,\omega )$$ h ( i , ω ) , the corresponding results for the effects of parameters (d,r,c,$$\alpha$$ α ) on average abundance function $$X_{A}(\omega )$$ X A ( ω ) have been explained.

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“…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]).…”

Section: Introductionmentioning

confidence: 99%

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

Yang

Kim

et al. 2019

New J. Phys.

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Real networks are not only multi-layered yet also dynamic. The role of coordinated network evolution regarding dynamic multi-layer networks where both network and strategy evolution simultaneously show diverse interdependence by layers remains poorly addressed. Here, we propose a general and simple coevolution framework to analyze how coordination of different dynamical processes affects strategy propagation in synergistically evolving interdependent networks. The strategic feedback constitutes the main driving force of network evolution yet the inherent cross-layer self-optimization functions as its compensation. We show that these two ingredients often catalyze a better performance of network evolution in propagating cooperation. Coordinated network evolution may be a doubleedged sword to cooperation and the network-adapting rate plays a crucial role in flipping its doublesided effect. It often economizes the cost and time consumption for driving the system to the full cooperation phase. Importantly, strongly coupled slow-tuned networks can outperform weakly coupled fast-regulated networks in solving social dilemmas, highlighting the fundamental advantages of coordinated network evolution and the importance of synergistic effect of dynamical processes in upholding human cooperation in multiplex networks.

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Coevolutionary dynamics of aspiration and strategy in spatial repeated public goods games

Cited by 54 publications

References 57 publications

Competition and partnership between conformity and payoff-based imitations in social dilemmas

Competition and partnership between conformity and payoff-based imitations in social dilemmas

The characteristics of average abundance function with mutation of multi-player threshold public goods evolutionary game model under redistribution mechanism

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

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