Reputation-based mutual selection rule promotes cooperation in spatial threshold public goods games

Most previous studies involving public goods games are investigated under a simplifying assumption that participation is either compulsive or unidirectional optional in collective interactions. Nevertheless, how the mutual selection rule, a more realistic participation mode, affects the evolution of cooperation in structured populations is still unclear. Here we introduce a reputation-based mutual selection rule for constituting participant groups into spatial threshold public goods games, where the public goods game can be conducted only if the participant number is not less than the threshold parameter. Interestingly, we find that moderate tolerance range results in the best environment for cooperators’ viability. Also, we show that lower member threshold is favorable for the evolution of cooperation, and correspondingly provide some typical snapshots for defectors, “active” cooperators (cooperators on which the public goods games are successfully conducted), and “inactive” cooperators. Moreover, we investigate the effects of memory factor in individuals’ reputation updating on the evolution of cooperation. Our work may provide an appropriate and alternative perspective in understanding the widespread cooperative behaviors in some realistic situations.     

The different cooperative behaviors on a kind of scale-free networks with identical degree sequence

The power-law degree distribution of scale-free networks plays an important role in the bloom of cooperation in the evolutionary games performed on them. In this paper we apply prisoner’s dilemma and public goods game on a family of scale-free networks with the same degree sequence, and show that power-law behavior alone does not determine the cooperative behavior in scale-free networks. Instead, we present that the direct connections among large-degree nodes have a crucial influence on the evolution of cooperation in the scale-free network family.     

Combining evolutionary game theory and network theory to analyze human cooperation patterns

As natural systems continuously evolve, the human cooperation dilemma represents an increasingly more challenging question. Humans cooperate in natural and social systems, but how it happens and what are the mechanisms which rule the emergence of cooperation, represent an open and fascinating issue. In this work, we investigate the evolution of cooperation through the analysis of the evolutionary dynamics of behaviours within the social network, where nodes can choose to cooperate or defect following the classical social dilemmas represented by Prisoner’s Dilemma and Snowdrift games. To this aim, we introduce a sociological concept and statistical estimator, “Critical Mass”, to detect the minimum initial seed of cooperators able to trigger the diffusion process, and the centrality measure to select within the social network. Selecting different spatial configurations of the Critical Mass nodes, we highlight how the emergence of cooperation can be influenced by this spatial choice of the initial core in the network. Moreover, we target to shed light how the concept of homophily, a social shaping factor for which “birds of a feather flock together”, can affect the evolutionary process. Our findings show that homophily allows speeding up the diffusion process and make quicker the convergence towards human cooperation, while centrality measure and thus the Critical Mass selection, play a key role in the evolution showing how the spatial configurations can create some hidden patterns, partially counterbalancing the impact of homophily.     

Effect of local information within network layers on the evolution of cooperation in duplex public goods games

Traditional works of public goods game (PGG) are often studied in simplex networks where agents play games through the same type of social interactions. In order to promote cooperation against the defection in PGGs in simplex network environment, many mechanisms have been proposed from different perspectives, such as the volunteering mechanisms, and the punishment and reward approaches. However, due to diverse types of interactions between agents in reality, the study of PGG should also consider the characteristic of multiplexity of networks. Hence, we firstly model the public goods game in the duplex network (for simplification of analysis, the duplex network is considered), in which agents have two types of social interactions, and thus the network is modeled as two network layers. This type of PGG is naturally named as duplex public goods game (D-PGG), in which agents can select one of the network layers to allocate their limited resources. Then for the new game environment (D-PGG), we propose a novel perspective to promote cooperation: degrading the information integrity, i.e., agents get information just from one network layer (local information) rather than from the whole duplex network (global information) in the evolution process. Finally, through theoretical analyses and simulations, we find that if agents imitate based on the local information of the payoff in the evolution, cooperation can be generally promoted; and the extent of promotion depends on both the network structure and the similarity of the network layers.     

How the expanded crowd-funding mechanism of some southern rural areas in China affects cooperative behaviors in threshold public goods game

The pursuit of high cooperation rates in public goods games has attracted many researchers. However, few researchers attach much weight to the influence of emotions on decision-making, especially on public goods games. From ancient to modern times, publishing the list of cooperators to stimulate cooperation has been a common phenomenon in some southern rural areas in China. Actually, the published list can influence individuals’ behaviors by affecting their emotions. Here we extend the method of publishing the list and optimize it by adding a lobbyist mechanism. Through numerical simulations, we find that the role of lobbyists can not be ignored unless the synergy factor is larger than a certain value. Additionally, we find that publishing the list certainly has a great effect on individual’s cooperative behavior. But whether to publish the list or not and how to publish the list depend on the situation.     

Does migration cost influence cooperation among success-driven individuals?

Migration as an important social factor has been recently considered in evolutionary games on graphs. However, the migration-related cost is largely ignored in previous works, which may indeed influence individual migration decision in human society. Here we propose a model of the success-driven migration with migration costs where individuals decide whether to migrate or not according to the migration cost and expected payoff. We consider two different calculation schemes for the migration cost, i.e., distance-dependent and distance-independent costs, and study their effects on the evolution of cooperation in the spatial prisoner’s dilemma, respectively. It is found that although the migration cost inhibits the migration of individuals, it does not necessarily lead to the suppression of cooperation. We explain the phenomenon by investigating the spatial patterns of cooperators and defectors. Interestingly, the curves of cooperation exhibit step structures and the corresponding heuristic analysis is provided. Our work complements previous studies and deepens the understanding regarding the success-driven migration on the evolution of cooperation.     

An improved public goods game model with reputation effect on the spatial lattices

How to model the evolution of cooperation within the population is an important and interdisciplinary issue across the academia. In this paper, we propose an improved public goods game model with reputation effect on spatial lattices to investigate the evolution of cooperation regarding the allocation of public resources. In our model, we modify the individual utility or fitness as a product of the present payoff and reputation-related power function, and strategy update adopts a Fermi-like probability function during the game evolution. Meanwhile, for an interaction between a pair of partners, the reputation of a cooperative agent will be accrued beyond two units, but the defective player will decrease his reputation by one unit. Extensive Monte Carlo numerical simulations indicate the introduction of reputation will foster the formation of cooperative clusters, and greatly enhance the level of public cooperation on the spatial lattices. The larger reputation factor leads to the higher cooperation level since the reputation effect will be enormously embedded into the utility evaluation under this scenario. The current results are vastly beneficial to understand the persistence and emergence of cooperation among many natural, social and synthetic systems, and also provide some useful suggestions to devise the feasible social governance measures and modes for the public resources or affairs.     

Prisoner's dilemma and clusters on small‐world networks

The structure of interaction plays an important role in the outcome of evolutionary games. This study investigates the evolution of stochastic strategies of the prisoner's dilemma played on structures ranging from lattices to small world networks. Strategies and payoffs are analyzed as a function of the network characteristics of the node they are playing on. Nodes with lattice‐like neighborhoods tend to perform better than the nodes modified during the rewiring process of the construction of the small‐world network. © 2007 Wiley Periodicals, Inc. Complexity 12:22–36, 2006     

演化博弈与自组织合作

主要研究复杂网络上的演化博弈.首先研究具有社团结构的无标度网络上的演化囚徒困境博弈及Newman-Watts小世界网络中异质性对合作演化的影响.然后考察了在不同合作者和作弊者初始分布配置情况下,不同的初始比例条件对合作水平的影响,且在社会网络上研究了雪堆博弈中的合作演化.进一步地,讨论了网络拓扑和博弈动力学的共同演化问题和网络上演化囚徒困境中的强化学习问题.最后给出了复杂网络上演化博弈论的未来发展方向与应用前景.     

Some results on cooperative interval games

Uncertainty is a daily presence in the real world. It affects our decision-making and may have influence on cooperation. On many occasions, uncertainty is so severe that we can only predict some upper and lower bounds for the outcome of our actions, i.e. payoffs lie in some intervals. A suitable game theoretic model to support decision-making in collaborative situations with interval data is that of cooperative interval games. Solution concepts that associate with each cooperative interval game sets of interval allocations with appealing properties provide a natural way to capture the uncertainty of coalition values into the players’ payoffs. In this paper, the relations between some set-valued solution concepts using interval payoffs, namely the interval core, the interval dominance core, the square interval dominance core and the interval stable sets for cooperative interval games, are studied. It is shown that the interval core is the unique stable set on the class of convex interval games.     

Evolutionary games and matching rules

This study considers evolutionary games with non-uniformly random matching when interaction occurs in groups of \(n\ge 2\) individuals using pure strategies from a finite strategy set. In such models, groups with different compositions of individuals generally co-exist and the reproductive success (fitness) of a specific strategy varies with the frequencies of different group types. These frequencies crucially depend on the matching process. For arbitrary matching processes (called matching rules), we study Nash equilibrium and ESS in the associated population game and show that several results that are known to hold for population games under uniform random matching carry through to our setting. In our most novel contribution, we derive results on the efficiency of the Nash equilibria of population games and show that for any (fixed) payoff structure, there always exists some matching rule leading to average fitness maximization. Finally, we provide a series of applications to commonly studied normal-form games.     

Implementation of weighted values in hierarchical and horizontal cooperation structures

This paper studies a non-cooperative mechanism implementing a cooperative solution for a situation in which members of a society are subdivided into groups and/or coalitions and there is asymmetry among the individuals of the society. To describe hierarchical and horizontal cooperation structure simultaneously, we present unified classes of games, the games with social structure, and define a weighted value for these games. We show that our mechanism works in any zero-monotonic environment and implements the Shapley value, the weighted Shapley value, the Owen’s coalitional value, and the weighted coalitional value, in some special cases.     

Melioration learning in iterated public goods games: The impact of exploratory noise

Experimental observations in iterated public goods games are explained by a simple but empirically well-grounded model of long-term reinforcement learning. In many experiments, medium levels of cooperation at the beginning decrease with further repetitions. However, in some settings, the actors only slowly learn the individual benefits of defection. In the present model, the decay in cooperation is mitigated by high individual returns, a large group size or stability in the group’s composition. Results from agent-based simulations are presented, and the underlying mechanisms are disclosed. The proposed explanation stresses the role of exploratory noise: if multiple actors explore their alternatives simultaneously, the marginal benefit of defection diminishes and cooperation can be sustained.     

Subgame-consistent cooperative solutions in randomly furcating stochastic differential games

The paradigm of randomly-furcating stochastic differential games incorporates additional stochastic elements via randomly branching payoffs in stochastic differential games. This paper considers dynamically stable cooperative solutions in randomly furcating stochastic differential games. Analytically tractable payoff distribution procedures contingent upon specific random realizations of the state and payoff structure are derived. This new approach widens the application of cooperative differential game theory to problems where the evolution of the state and future environments are not known with certainty. Important cases abound in regional economic cooperation, corporate joint ventures and environmental control. An illustration in cooperative resource extraction is presented.     

Dynamic equilibria of group vaccination strategies in a heterogeneous population

In this paper we present an evolutionary variational inequality model of vaccination strategies games in a population with a known vaccine coverage profile over a certain time interval. The population is considered to be heterogeneous, namely its individuals are divided into a finite number of distinct population groups, where each group has different perceptions of vaccine and disease risks. Previous game theoretical analyses of vaccinating behaviour have studied the strategic interaction between individuals attempting to maximize their health states, in situations where an individual’s health state depends upon the vaccination decisions of others due to the presence of herd immunity. Here we extend such analyses by applying the theory of evolutionary variational inequalities (EVI) to a (one parameter) family of generalized vaccination games. An EVI is used to provide conditions for existence of solutions (generalized Nash equilibria) for the family of vaccination games, while a projected dynamical system is used to compute approximate solutions of the EVI problem. In particular we study a population model with two groups, where the size of one group is strictly larger than the size of the other group (a majority/minority population). The smaller group is considered much less vaccination inclined than the larger group. Under these hypotheses, considering that the vaccine coverage of the entire population is measured during a vaccine scare period, we find that our model reproduces a feature of real populations: the vaccine averse minority will react immediately to a vaccine scare by dropping their strategy to a nonvaccinator one; the vaccine inclined majority does not follow a nonvaccinator strategy during the scare, although vaccination in this group decreases as well. Moreover we find that there is a delay in the majority’s reaction to the scare. This is the first time EVI problems are used in the context of mathematical epidemiology. The results presented emphasize the important role played by social heterogeneity in vaccination behaviour, while also highlighting the valuable role that can be played by EVI in this area of research.      

Evolutionary games with facilitators: When does selection favor cooperation?

We study the combined influence of selection and random fluctuations on the evolutionary dynamics of two-strategy (“cooperation” and “defection”) games in populations comprising cooperation facilitators. The latter are individuals that support cooperation by enhancing the reproductive potential of cooperators relative to the fitness of defectors. By computing the fixation probability of a single cooperator in finite and well-mixed populations that include a fixed number of facilitators, and by using mean field analysis, we determine when selection promotes cooperation in the important classes of prisoner’s dilemma, snowdrift and stag-hunt games. In particular, we identify the circumstances under which selection favors the replacement and invasion of defection by cooperation. Our findings, corroborated by stochastic simulations, show that the spread of cooperation can be promoted through various scenarios when the density of facilitators exceeds a critical value whose dependence on the population size and selection strength is analyzed. We also determine under which conditions cooperation is more likely to replace defection than vice versa.     

Mutual punishment promotes cooperation in the spatial public goods game

Punishment has been proved to be an effective mechanism to sustain cooperation among selfish individuals. In previous studies, punishment is unidirectional: an individual i can punish j but j cannot punish i. In this paper, we propose a mechanism of mutual punishment, in which the two individuals will punish each other if their strategies are different. Because of the symmetry in imposing the punishment, one might expect intuitively the strategy to have little effect on cooperation. Surprisingly, we find that the mutual punishment can promote cooperation in the spatial public goods game. Other pertinent quantities such as the time evolution of cooperator density and the spatial distribution of cooperators and defectors are also investigated.     

From hierarchies to levels: new solutions for games with hierarchical structure

Recently, applications of cooperative game theory to economic allocation problems have gained popularity. In many of these problems, players are organized according to either a hierarchical structure or a levels structure that restrict the players’ possibilities to cooperate. In this paper, we propose three new solutions for games with hierarchical structure and characterize them by properties that relate a player’s payoff to the payoffs of other players located in specific positions in the hierarchical structure relative to that player. To define each solution, we consider a certain mapping that transforms the hierarchical structure into a levels structure, and then we apply the standard generalization of the Shapley value to the class of games with levels structure. Such transformation mappings are studied by means of properties that relate a player’s position in both types of structure.     

The Compromise Value for Cooperative Games with Random Payoffs

This paper introduces and studies the compromise value for cooperative games with random payoffs, that is, for cooperative games where the payoff to a coalition of players is a random variable. This value is a compromise between utopia payoffs and minimal rights and its definition is based on the compromise value for NTU games and the τ-value for TU games. It is shown that the nonempty core of a cooperative game with random payoffs is bounded by the utopia payoffs and the minimal rights. Consequently, for such games the compromise value exists. Further, we show that the compromise value of a cooperative game with random payoffs coincides with the τ-value of a related TU game if the players have a certain type of preferences. Finally, the compromise value and the marginal value, which is defined as the average of the marginal vectors, coincide on the class of two-person games. This results in a characterization of the compromise value for two-person games.I thank Peter Borm, Ruud Hendrickx and two anonymous referees for their valuable comments.     

Evolutionary Selection of Socially Sensitive Preferences in Random Matching Environments

In this paper we study the evolutionary selection of socially sensitive preferences in the context of reference interaction settings such as coordination failure and cooperation. We refer to a specific class of socially sensitive preferences in which players weigh additively their own material payoff against the opponent with either a positive or negative coefficient (λ-players). Preference evolution is guided by replicator dynamics in a context of perfect observability of preferences types and stochastic pairwise matching. We take an indirect evolutionary approach, that is, the selection mechanism operates on the actual material payoffs earned by players, so that any instance of socially sensitive preference can be thought of as instrumentally maintained. We find that the evolutionary viability of socially sensitive preferences basically depends on whether or not they cause a substantial improvement in the achievement of socially efficient outcomes with respect to the case where only self-serving or unconditionally focused preference orientations are observed. Our results suggest that moderate pro-social preference orientations are likely to emerge from social selection even in the absence of an intrinsic motivational drive, whereas extremely pro-social orientations as well as competitive and anti-social ones may need a stronger motivational base.