Dynamic scale return coefficient with environmental feedback promotes cooperation in spatial public goods game

Abstract

In the traditional spatial public goods game (SPGG), the total contributions of each group are linearly amplified by the same enhancement factor, which does not coincide with the real situation. Although some literature has considered the non-linearity and heterogeneity of scale returns between groups, the dierences are completely generated by stochastic mechanisms. In addition, the coecient will not change once assigned in previous studies. In this paper, we consider an environmental feedback mechanism and introduce a dynamic scale return coecient into the payo function. We observe that people who have a good record of cooperation working together can produce greater synergies and can have a larger return coecient. We use the concept of reputation to describe individuals' historical cooperation records. Therefore, we assume that the scale return coecient is governed by the dierence between the average reputation of the group and the whole population, which will also evolve over time. In addition, we set a reputation amplitude to control the extent to which reputation dierences between groups aect payos. By simulation experiments, we reveal that dynamic scale return coecient based

Reputation preferences resolve social dilemmas in spatial multigames

“…Evolutionary game theory has supplied a universal framework to clarify how cooperation emerges, maintains and spreads among selfish individuals [3,4]. Within this framework, various famous game models including, but not limited to, the prisoner's dilemma game (PDG) [5,6], the snowdrift game (SDG) [7,8] and the public goods game (PGG) [9][10][11][12], have been commonly used to address various social dilemmas and make fruitful achievements [13][14][15][16], especially in the field of artificial intelligence [17,18]. In particular, the pioneering work by Nowak and May [19] and the fast development of complex networks [20,21] have further stimulated the investigation of evolutionary games using square lattice [14,22], small-world [23,24], and scale-free [25,26] networks, although a previous work [27] demonstrated that a square lattice might inhibit the evolution of cooperation in the SDG.…”

How to evaluate one's behavior toward ‘bad’ individuals? Exploring good social norms in promoting cooperation in spatial public goods games

“…Statistical physics provides a powerful tool in this direction [15,16]. Along this line of research, many micromechanisms for promoting cooperation have been proposed, such as introducing reward and punishment [17][18][19][20][21][22][23][24][25][26][27], social exclusion [28][29][30][31][32][33][34], considering individual or group heterogeneity [35][36][37][38][39], intelligent learning [40][41][42][43], and so on. Essentially, these mechanisms change the payoff structure of strategies or the rules of strategy updating.…”