Rawlsian altruism with perfect discrimination leads to social efficiency

Recent studies draw attention on the highly specialized capacity of human beings in recognizing altruists versus cheaters in social interactions. These results hint at the existence of specialized abilities that support discriminating behavior in strategic interactions. In this paper, we explore the implications of discriminating behavior in the study of the indirect evolutionary selection of selfish versus altruistic motivations in the context of generic 2×2 base games, and in particular for coordination and cooperation scenarios. We find that inequality averse (Rawlsian) altruism can enforce under rather general conditions socially optimal outcomes, including cases where selfishness cannot, such as in prisoner’s dilemmas. Inequality seeking (Nietzschian) altruism in no case improves upon Rawlsian altruism in terms of social optimality of outcomes, and often does worse. In the cooperation scenario in particular, Nietzschean altruism never manages to implement the cooperative outcome. Under perfect discrimination, moreover, inequality averse (Rawlsian) altruism often evolves at the expense of selfishness. These results suggest that the development of sophisticated discrimination abilities may be strongly adaptive in supporting fairness-oriented forms of pro-sociality in humans in the context of social dilemmas and coordination problems.     

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.     

Towards the evolution of social structure

To what extent can social structure result from evolutionary processes as popposed to being deliberately organised? To begin to answer this questions five different but releated social simulations are reviewed, and a map of which mechanisms might results in what structures under what conditions being started. These show that different structures can be brought about by evolutionary processes based on the abilities and propensities of the individuals. The article ends with some challenges—to construct a credible simulations of more sophisticated structures: social group selection and self-organised value chains.     

Noise-induced enhancement of network reciprocity in social dilemmas

The network reciprocity is an important dynamic rule fostering the emergence of cooperation among selfish individuals. This was reported firstly in the seminal work of Nowak and May, where individuals were arranged on the regular lattice network, and played the prisoner’s dilemma game (PDG). In the standard PDG, one often assumes that the players have perfect rationality. However, in reality, we human are far from rational agents, as we often make mistakes, and behave irrationally. Accordingly, in this work, we introduce the element of noise into the measurement of fitness, which is determined by the parameter α controlling the degree of noise. The considered noise-induced mechanism remarkably promotes the behavior of cooperation, which may be conducive to interpret the emergence of cooperation within the population.     

Colony and evolutionary dynamics of a two‐stage model with brood cannibalism and division of labor in social insects

Division of labor (DOL) is a major factor for the great success of social insects because it increases the efficiency of a social group where different individuals perform different tasks repeatedly and presumably with increased performance. Cannibalism plays an important role in regulating colony growth and development by regulating the number of individuals in a colony and increasing survival by providing access to essential nutrients and minimizing competition among colony mates. To understand the synergy effects of DOL and cannibalistic behavior on colony dynamic outcomes, we propose and study a compartmental two‐stage model using ecological and evolutionary game theory settings. Our analytical results of the ecological and evolutionary models suggest that: (1) A noncannibalistic colony can survive if the efficiency of energy investment reflecting the DOL is greater than the relative death rate of the older population. (2) A cannibalistic colony can die out if both the efficiency of energy investment and the relative cannibalism rate (where each is also reflecting the DOL) are too large; or if the relative cannibalism rate alone is too small. (3) From our numerical analysis, cannibalism can increase or reduce the colony's total population size, which greatly depends on the benefit of egg cannibalism increasing or decreasing of adult's lifespan. (4) A cannibalistic and noncannibalistic colony can experience bistability due to cooperative behavior. (5) In the evolutionary settings, DOL can prevent colony death and natural selection can preserve strong Allee effects by selecting the traits with the largest investment on brood care and the lowest cannibalism rate. (6) Evolutionary dynamics may increase the fitness of the colony, i.e., the successful production of workforce which results in the increase of total worker population size, colony survival, and reproduction. Our results suggest both cannibalism and DOLs are adaptive strategies that increase the size of the worker population, and therefore, persistence of the colony.     

Role of update dynamics in the collective cooperation on the spatial snowdrift games: Beyond unconditional imitation and replicator dynamics

In this paper, we investigate the role of update or imitation rules in the spatial snowdrift game on regular lattices. Three different update rules, including unconditional imitation (UI), replicator dynamics (RD) and the Moran process, are utilized to update the strategies of focal players during the game process in the spatial snowdrift on the lattice. We observe that the aggregate cooperation level between players is largely elevated by using the Moran process in the spatial snowdrift game, when compared to the UI or replicator dynamics. Meanwhile, we carefully explore the dynamical evolution of frequency of cooperators and the cluster formation pattern for these three update rules. Moreover, it is also shown that the evolutionary behavior under the Moran update is independent of and insensitive to the randomly initial configurations of cooperators and defectors. The current results clearly indicate that the introduction of moderate randomness in the strategy update will highly promote the maintenance and persistence of cooperation among selfish individuals, which will be greatly instrumental to deeply understand the evolution of cooperation within many natural, biological and social systems.     

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.     

The Cultural Evolution of Indiscriminate Altruism in a Large Randomly Matching Population

Altruism is hard to explain because altruistic acts are costly to the individuals who perform them. Although past work has identified conditions under which altruism can evolve, there is wide agreement among evolutionary theorists in the social sciences and biology that indiscriminate altruism cannot evolve in a large randomly matching population. Building on earlier work (Mark, 2002 Mark , N. P. ( 2002 ). Cultural transmission, disproportionate acquisition, and the evolution of cooperation . American Sociological Review , 67 , 323 – 344 .[Crossref], [Web of Science ®] , [Google Scholar]), I show that cultural transmission can create a cultural evolutionary force toward indiscriminate altruism in a large randomly matching population. The cultural transmission of a behavior (altruistic or selfish) disproportionately exposes those who acquire that behavior to that behavior prior to its acquisition. That is, individuals who have acquired an altruistic behavior through cultural transmission (i.e., who learned to behave altruistically from other people) were disproportionately exposed to the altruistic acts of others. Likewise, individuals who have acquired a selfish behavior through cultural transmission were disproportionately exposed to the selfish acts of others. Because of this disproportionate prior exposure, altruists have disproportionately benefitted from the altruistic acts of others, and selfish individuals have disproportionately been hurt by the selfish acts of others. If the benefits of being the target of altruistic acts increase one's attractiveness as a behavioral model, then a cultural evolutionary force toward altruism results.

[An appendix to the article is featured as an online supplement at the publisher's website.]     

Evolution in spatial predator–prey models and the “prudent predator”: The inadequacy of steady‐state organism fitness and the concept of individual and group selection

We review recent research which reveals: (1) how spatially distributed populations avoid overexploiting resources due to the local extinction of over‐exploitative variants, and (2) how the conventional understanding of evolutionary processes is violated by spatial populations so that basic concepts, including fitness assignment to individual organisms, are not applicable, and even kin and group selection are unable to describe the mechanism by which exploitative behavior is bounded. To understand these evolutionary processes, a broader view is needed of the properties of multiscale spatiotemporal patterns in organism–environment interactions. We discuss measures that quantify the effects of these interactions on the evolution of a population, including multigenerational fitness and the heritability of the environment. © 2008 Wiley Periodicals, Inc. Complexity, 2008.     

协同创新主体合作的演化博弈及政府干预的仿真

文章首先基于演化博弈理论,研究了无政府干预下协同创新主体采取合作策略的演化博弈规律;其次基于系统动力学理论,分析了政府干预下协同创新主体采取合作策略的演化博弈规律,并构建了系统动力学模型及运用Vensim软件作出了仿真分析。仿真发现,协同创新主体间的合作主要受政府惩罚力度、采取的惩罚机制以及创新主体采取投机行为所产生的生产成本的影响。因此,政府提高惩罚力度并采用动态惩罚机制,能促使协同创新主体更快地采取合作策略进行协同创新。     

基于进化博弈视角的水源地与下游生态补偿合作演化分析

水源地与下游地方政府之间的协议合作可以协调流域上下游之间的矛盾和利益,是一种可实现流域生态保护良性循环的生态补偿尝试。本文应用进化博弈的双种群博弈理论,研究了水源地和下游地方政府之间博弈演化过程及影响因素。研究表明,流域上下游地方政府合作的演化方向主要受水源地不保护及下游不补偿受到的惩罚、下游对水源地的补偿额度、水源地和下游合作的初始成本、水源地生态保护的成本及收益等八个因素的影响。降低水源地的保护成本及水源地和下游合作的初始成本,提高水源地因保护而获得的综合效益、提高水源地不保护及下游不补偿受到的惩罚额度、合理确定下游对水源地的补偿额度将有利于水源地生态补偿机制向合作方向演进。     

Searching with cooperators

Biological evolution serves as a blueprint for the design of search and optimization algorithms, and has generated vast number of research prototypes as well as industrial implementations since it was first proposed to solve complex engineering problems the 1960s [1], [2], [3]. Underlying this is the idea that the evolutionary forces of mutation, recombination, reproduction and selection can drive the population towards better adapted solution over time, effectively solving an optimization problem by navigating the fitness landscape they inhabit. A much overlooked evolutionary force in the design of better algorithms so far has been cooperation, shown to be crucial to shape individual and group behavior at multiple scales of interaction. Here we explore the ability of cooperative dynamics to further increase the efficiency of evolutionary strategies. For this, we perform computer experiments on a variety of landscapes of increasing complexity. We present evidence suggesting that cooperative dynamics are able to naturally balance exploration and exploitation of local maxima, via endless cycles of cooperation (where local maxima are exploited) and defection (where new areas are explored). Cooperative strategies prove to be more robust to landscape ruggedness than evolutionary strategies which never cooperate, always cooperate, or cooperate randomly. Furthermore, our simulations show that the cooperative dynamics are invariant to the complexity of the landscape, hinting at the possibility that cooperation strategies may be able to absorb and exploit local information to keep the exploration–exploration tradeoff invariant across a range of environments.     

Norms of Cooperation in a Game of Partnership

We study a model of partnership with costly commitment in an evolutionary game-theoretic framework. We introduce various types of cooperative players with different degrees of strategic sophistication. We find that a necessary condition for cooperation at the social equilibrium is that the probability of a high opportunity value falls below a certain critical threshold. Such condition, however, is not sufficient. If players are too naively cooperative, the permanence of cooperation at the equilibrium is put at risk because naive cooperation entails playing inefficient responses to other equilibrium strategies. As a consequence, naive cooperation will be present at the equilibrium selected by the social dynamics only under somewhat special conditions. If cooperators are more flexible, in that they remain in the partnership only if mated to a first stage cooperator and only in lack of favorable outside opportunities, cooperation is almost granted provided that it is Pareto efficient (perverse lock in cases under unfavorable initial conditions are possible). Finally, the selection of Pareto superior cooperation with certainty may be granted by a certain norm-oriented type of strategically sophisticated behavior, that we call Rawlsian altruism.     

团队规范下管制员违章行为演化与监管研究

为发现团队规范下管制员违章行为及监管策略的演化博弈规律,运用演化博弈理论,构建安全管理者与管制员演化博弈模型,分析博弈系统均衡点的局部稳定性。在此基础上建立演化博弈的系统动力学模型,仿真模拟不同情形下博弈双方策略选择的动态演化过程,并分析模型参数变化对系统演化结果的影响。结果表明:正的团队规范有助于系统演化至理想模式,负的团队规范会使系统陷入“不良锁定”模式和“震荡”模式;管制员行为收益、行为成本、被监查到的概率、处罚力度、监管成本等因素均对系统演化结果产生影响。鼓励班组成员对违章行为进行否定性评价、加大对管制员的处罚力度等均能够长效促进管制员主动遵章。     

Cooperation among mobile individuals with payoff expectations in the spatial prisoner’s dilemma game

We propose a model to address the problem how the evolution of cooperation in a social system depends on the spatial motion and the payoff expectation. In the model, if the actual payoff of an individual is smaller than its payoff expectation, the individual will either move to a new site or simply reverse its current strategy. It turns out that migration of dissatisfied individuals with relatively low expectation level leads to the aggregation of cooperators and promotion of cooperation. Moreover, under appropriate parameters migration leads to some interesting spatiotemporal patterns which seems not to have been reported in previously studied spatial games. Furthermore, it also found that a population with constant expectation can better favor cooperative behavior than a population with adaptive aspiration.     

自适应多种群回溯群居蜘蛛算法求解TSP问题

在群居蜘蛛优化算法中引入自适应决策半径,将蜘蛛种群动态地分成多个种群,种群内适应度不同的个体采取不同的更新方式.在筛选全局极值的基础上,根据进化程度执行回溯迭代更新,提出一种自适应多种群回溯群居蜘蛛优化算法,旨在提高种群样本多样性和算法全局寻优能力.函数寻优结果表明改进算法具有较快的收敛速度和较高的收敛精度.最后将其应用于TSP问题的求解.     

An approach for relating social structure to cognitive structure

There are three different reasons why non-linear functions between social macro-variables (aggregates) may arise. They can be related to three basic steps of a specific model of explanation of social phenomena, defined by Coleman: the logic of situation, the logic of selection and the logic of transition. Starting with a model of one linear difference equation, a change to three different non-linear system equations can generate stable cycles, bifurcations, and chaos. These non-linear system equations can be deduced from simple assumptions about individual or institutional social attributes. It is shown that a) non-linear individual reactions, b) different selection rules for actors having different social attributes and c) institutional constraints resulting in different transition processes are possible causes for non-linearity at the system level. Furthermore it is demonstrated that the assumption of non-linear but homogeneous reactions of all persons have a similar effect on non-linearity, like it is the case for different selection rules. However, despite of being able to show mathematically the possibility of chaos, it has to be said that chaos as a durable state of social systems is very improbable.     

PPP项目中非完全利益群体的合作形成机制研究

协调政府与社会资本合作的利益分歧,进而实现个体理性向集体理性的趋同,这是纾解PPP项目合作困境的切入点之一。基于合作博弈理论,本文构建PPP项目非完全利益群体的合作形成机制,分析政府与社会资本间“合作共赢”的必要因素。研究表明,由政府与社会资本组成的PPP项目非完全利益群体,可在“理性-效用转移-有效协商”机制的协同作用下主动采取最优合作策略。其中,理性机制验证了政府与社会资本达成合作意向的前提,效用转移机制可实现二者之间的风险-收益对等,有效协商机制将达成政府与社会资本合作的帕累托均衡。