Cooperation prevails when individuals adjust their social ties

Conventional evolutionary game theory predicts that natural selection favours the selfish and strong even though cooperative interactions thrive at all levels of organization in living systems. Recent investigations demonstrated that a limiting factor for the evolution of cooperative interactions is the way in which they are organized, cooperators becoming evolutionarily competitive whenever individuals are constrained to interact with few others along the edges of networks with low average connectivity. Despite this insight, the conundrum of cooperation remains since recent empirical data shows that real networks exhibit typically high average connectivity and associated single-to-broad–scale heterogeneity. Here, a computational model is constructed in which individuals are able to self-organize both their strategy and their social ties throughout evolution, based exclusively on their self-interest. We show that the entangled evolution of individual strategy and network structure constitutes a key mechanism for the sustainability of cooperation in social networks. For a given average connectivity of the population, there is a critical value for the ratio W between the time scales associated with the evolution of strategy and of structure above which cooperators wipe out defectors. Moreover, the emerging social networks exhibit an overall heterogeneity that accounts very well for the diversity of patterns recently found in acquired data on social networks. Finally, heterogeneity is found to become maximal when W reaches its critical value. These results show that simple topological dynamics reflecting the individual capacity for self-organization of social ties can produce realistic networks of high average connectivity with associated single-to-broad–scale heterogeneity. On the other hand, they show that cooperation cannot evolve as a result of “social viscosity” alone in heterogeneous networks with high average connectivity, requiring the additional mechanism of topological co-evolution to ensure the survival of cooperative behaviour.     

Fashion,Cooperation, and Social Interactions

Fashion plays such a crucial rule in the evolution of culture and society that it is regarded as a second nature to the human being. Also, its impact on economy is quite nontrivial. On what is fashionable, interestingly, there are two viewpoints that are both extremely widespread but almost opposite: conformists think that what is popular is fashionable, while rebels believe that being different is the essence. Fashion color is fashionable in the first sense, and Lady Gaga in the second. We investigate a model where the population consists of the afore-mentioned two groups of people that are located on social networks (a spatial cellular automata network and small-world networks). This model captures two fundamental kinds of social interactions (coordination and anti-coordination) simultaneously, and also has its own interest to game theory: it is a hybrid model of pure competition and pure cooperation. This is true because when a conformist meets a rebel, they play the zero sum matching pennies game, which is pure competition. When two conformists (rebels) meet, they play the (anti-) coordination game, which is pure cooperation. Simulation shows that simple social interactions greatly promote cooperation: in most cases people can reach an extraordinarily high level of cooperation, through a selfish, myopic, naive, and local interacting dynamic (the best response dynamic). We find that degree of synchronization also plays a critical role, but mostly on the negative side. Four indices, namely cooperation degree, average satisfaction degree, equilibrium ratio and complete ratio, are defined and applied to measure people’s cooperation levels from various angles. Phase transition, as well as emergence of many interesting geographic patterns in the cellular automata network, is also observed.     

Cooperation under indirect reciprocity and imitative trust

Indirect reciprocity, a key concept in behavioral experiments and evolutionary game theory, provides a mechanism that allows reciprocal altruism to emerge in a population of self-regarding individuals even when repeated interactions between pairs of actors are unlikely. Recent empirical evidence show that humans typically follow complex assessment strategies involving both reciprocity and social imitation when making cooperative decisions. However, currently, we have no systematic understanding of how imitation, a mechanism that may also generate negative effects via a process of cumulative advantage, affects cooperation when repeated interactions are unlikely or information about a recipient's reputation is unavailable. Here we extend existing evolutionary models, which use an image score for reputation to track how individuals cooperate by contributing resources, by introducing a new imitative-trust score, which tracks whether actors have been the recipients of cooperation in the past. We show that imitative trust can co-exist with indirect reciprocity mechanisms up to a threshold and then cooperation reverses -revealing the elusive nature of cooperation. Moreover, we find that when information about a recipient's reputation is limited, trusting the action of third parties towards her (i.e. imitating) does favor a higher collective cooperation compared to random-trusting and share-alike mechanisms. We believe these results shed new light on the factors favoring social imitation as an adaptive mechanism in populations of cooperating social actors.     

Stable public goods cooperation and dynamic social interactions in yeast

Despite long-standing theoretical interest in the evolution of cooperation, empirical data on the evolutionary dynamics of cooperative traits remain limited. Here, we investigate the evolutionary dynamics of a simple public goods cooperative trait, invertase secretion, using a long-term selection experiment in Saccharomyces cerevisiae. We show that average investment in cooperation remains essentially constant over a period of hundreds of generations in viscous populations with high relatedness. Average cooperation remains constant despite transient local selection for high and low levels of cooperation that generate dynamic social interactions. Natural populations of yeast show similar variation in social strategies, which is consistent with the existence of similar selective pressures on public goods cooperation in nature.     

Cooperation can promote rescue or lead to evolutionary suicide during environmental change

The adaptation of populations to changing conditions may be affected by interactions between individuals. For example, when cooperative interactions increase fecundity, they may allow populations to maintain high densities and thus keep track of moving environmental optima. Simultaneously, changes in population density alter the marginal benefits of cooperative investments, creating a feedback loop between population dynamics and the evolution of cooperation. Here we model how the evolution of cooperation interacts with adaptation to changing environments. We hypothesize that environmental change lowers population size and thus promotes the evolution of cooperation, and that this, in turn, helps the population keep up with the moving optimum. However, we find that the evolution of cooperation can have qualitatively different effects, depending on which fitness component is reduced by the costs of cooperation. If the costs decrease fecundity, cooperation indeed speeds adaptation by increasing population density; if, in contrast, the costs decrease viability, cooperation may instead slow adaptation by lowering the effective population size, leading to evolutionary suicide. Thus, cooperation can either promote or—counterintuitively—hinder adaptation to a changing environment. Finally, we show that our model can also be generalized to other social interactions by discussing the evolution of competition during environmental change.     

Participation costs dismiss the advantage of heterogeneous networks in evolution of cooperation

Real social interactions occur on networks in which each individual is connected to some, but not all, of others. In social dilemma games with a fixed population size, heterogeneity in the number of contacts per player is known to promote evolution of cooperation. Under a common assumption of positively biased pay-off structure, well-connected players earn much by playing frequently, and cooperation once adopted by well-connected players is unbeatable and spreads to others. However, maintaining a social contact can be costly, which would prevent local pay-offs from being positively biased. In replicator-type evolutionary dynamics, it is shown that even a relatively small participation cost extinguishes the merit of heterogeneous networks in terms of cooperation. In this situation, more connected players earn less so that they are no longer spreaders of cooperation. Instead, those with fewer contacts win and guide the evolution. The participation cost, or the baseline pay-off, is irrelevant in homogeneous populations, but is essential for evolutionary games on heterogeneous networks.     

Evolutionary game theory meets social science: Is there a unifying rule for human cooperation?

Evolutionary game theory has shown that human cooperation thrives in different types of social interactions with a PD structure. Models treat the cooperative strategies within the different frameworks as discrete entities and sometimes even as contenders. Whereas strong reciprocity was acclaimed as superior to classic reciprocity for its ability to defeat defectors in public goods games, recent experiments and simulations show that costly punishment fails to promote cooperation in the IR and DR games, where classic reciprocity succeeds. My aim is to show that cooperative strategies across frameworks are capable of a unified treatment, for they are governed by a common underlying rule or norm. An analysis of the reputation and action rules that govern some representative cooperative strategies both in models and in economic experiments confirms that the different frameworks share a conditional action rule and several reputation rules. The common conditional rule contains an option between costly punishment and withholding benefits that provides alternative enforcement methods against defectors. Depending on the framework, individuals can switch to the appropriate strategy and method of enforcement. The stability of human cooperation looks more promising if one mechanism controls successful strategies across frameworks.     

Joint Effects of Asymmetric Payoff and Reciprocity Mechanisms on Collective Cooperation in Water Sharing Interactions: A Game Theoretic Perspective

Common-pool resource (CPR) dilemmas distinguish themselves from general public good problems by encompassing both social and physical features. This paper examines how a physical mechanism, namely asymmetric payoff; and a social mechanism, reciprocity; simultaneously affect collective cooperation in theoretical water sharing interactions. We present an iterative N-person game theoretic model to investigate the joint effects of these two mechanisms in a linear fully connected river system under three information assumptions. From a simple evolutionary perspective, this paper quantitatively addresses the conditions for Nash Equilibrium in which collective cooperation might be established. The results suggest that direct reciprocity increases every actor’s motivation to contribute to the collective good of the river system. Meanwhile, various upstream and downstream actors manifest individual disparities as a result of the direct reciprocity and asymmetric payoff mechanisms. More specifically, the downstream actors are less willing to cooperate unless there is a high probability that long-term interactions are ensured; however, a greater level of asymmetries is likely to increase upstream actors’ incentives to cooperate even though the interactions could quickly end. The upstream actors also display weak sensitivity to an increase in the total number of actors, which generally results in a reduction in the other actors’ motivation for cooperation. It is also shown that the indirect reciprocity mechanism relaxes the overall conditions for cooperative Nash Equilibrium.     

Kin selection may inhibit the evolution of reciprocation

Kin selection and reciprocal cooperation provide two candidate explanations for the evolution of cooperation. Models of the evolution of cooperation have typically focussed on one or the other mechanism, despite claims that kin selection could pave the way for the evolution of reciprocal cooperation. We describe a computer simulation model that explicitly supports both kin selection and reciprocal cooperation. The model simulates a viscous population of discrete individuals with social interaction taking the form of the Prisoner's Dilemma and selection acting on performance in these interactions. We recount how the analytical and empirical study of this model led to the conclusion that kin selection may actually inhibit the evolution of effective strategies for establishing reciprocal cooperation.     

Societal background influences social learning in cooperative decision making

Humans owe their ecological success to their great capacities for social learning and cooperation: learning from others helps individuals adjust to their environment and can promote cooperation in groups. Classic and recent studies indicate that the cultural organization of societies shapes the influence of social information on decision making and suggest that collectivist values (prioritizing the group relative to the individual) increase tendencies to conform to the majority. However, it is unknown whether and how societal background impacts social learning in cooperative interactions. Here we show that social learning in cooperative decision making systematically varies across two societies. We experimentally compare people's basic propensities for social learning in samples from a collectivist (China) and an individualist society (United Kingdom; total n?=?540) in a social dilemma and a coordination game. We demonstrate that Chinese participants base their cooperation decisions on information about their peers much more frequently than their British counterparts. Moreover, our results reveal remarkable societal differences in the type of peer information people consider. In contrast to the consensus view, Chinese participants tend to be substantially less majority-oriented than the British. While Chinese participants are inclined to adopt peer behavior that leads to higher payoffs, British participants tend to cooperate only if sufficiently many peers do so too. These results indicate that the basic processes underlying social transmission are not universal; rather, they vary with cultural conditions. As success-based learning is associated with selfish behavior and majority-based learning can help foster cooperation, our study suggests that in different societies social learning can play diverging roles in the emergence and maintenance of cooperation.     

The coevolution of long‐term pair bonds and cooperation

The evolution of social traits may not only depend on but also change the social structure of the population. In particular, the evolution of pairwise cooperation, such as biparental care, depends on the pair‐matching distribution of the population, and the latter often emerges as a collective outcome of individual pair‐bonding traits, which are also under selection. Here, we develop an analytical model and individual‐based simulations to study the coevolution of long‐term pair bonds and cooperation in parental care, where partners play a Snowdrift game in each breeding season. We illustrate that long‐term pair bonds may coevolve with cooperation when bonding cost is below a threshold. As long‐term pair bonds lead to assortative interactions through pair‐matching dynamics, they may promote the prevalence of cooperation. In addition to the pay‐off matrix of a single game, the evolutionarily stable equilibrium also depends on bonding cost and accidental divorce rate, and it is determined by a form of balancing selection because the benefit from pair‐bond maintenance diminishes as the frequency of cooperators increases. Our findings highlight the importance of ecological factors affecting social bonding cost and stability in understanding the coevolution of social behaviour and social structures, which may lead to the diversity of biological social systems.     

Female cleaner fish cooperate more with unfamiliar males

Joint group membership is of major importance for cooperation in humans, and close ties or familiarity with a partner are also thought to promote cooperation in other animals. Here, we present the opposite pattern: female cleaner fish, Labroides dimidiatus, behave more cooperatively (by feeding more against their preference) when paired with an unfamiliar male rather than with their social partner. We propose that cooperation based on asymmetric punishment causes this reversed pattern. Males are larger than and dominant to female partners and are more aggressive to unfamiliar than to familiar female partners. In response, females behave more cooperatively with unfamiliar male partners. Our data suggest that in asymmetric interactions, weaker players might behave more cooperatively with out-group members than with in-group members to avoid harsher punishment.     

Do descriptive social norms drive peer punishment? Conditional punishment strategies and their impact on cooperation

Peer punishment is widely considered a key mechanism supporting cooperation in human groups. Although much research shows that human behavior is shaped by the prevailing social norms, little is known about how punishment decisions are impacted by the social context. We present a set of large-scale incentivized experiments in which participants (999 American participants recruited via Amazon Mechanical Turk) could punish their partner conditional on either the level of cooperation or the level of punishment displayed by others who previously interacted in the same setting. While many participants punish independently of levels of cooperation or punishment, a substantial portion punishes free riding more severely when cooperation is more common (‘norm enforcement’), or when free riding is more severely punished by others (‘conformist punishment’). With a dynamic model we demonstrate that conditional punishment strategies can substantially promote cooperation. In particular, conformist punishment helps cooperation to gain a foothold in a population, and norm enforcement helps to maintain cooperation at high levels. Our results provide solid empirical evidence of conditional punishment strategies and illustrate their possible implications for the dynamics of human cooperation.     

Uncertainty causes humans to use social heuristics and to cooperate more: An experiment among Belgian university students

When humans engage in social interactions, they are often uncertain about what the possible outcomes are. Because of this, highly sophisticated cooperation strategies may not be very effective. Indeed, some models instead predict the emergence of ‘social heuristics’: simple cooperation strategies that perform well across a range of different situations. Here, we put these predictions to the test in a large-scale interactive decision making experiment. We confronted participants (mostly Belgian university students) with a broad range of cooperative interactions, systematically varying the uncertainty participants had about the consequences of cooperating. As expected, we find that uncertainty about the payoff consequences of cooperation causes individuals to use social heuristics. Additionally, these heuristics directly cause a marked increase in cooperation compared to the treatment without uncertainty, even in situations where cooperation can never be beneficial. These findings provide a new explanation for why human social behavior often violates the standard predictions of economic and evolutionary theory.     

Movement patterns, social dynamics, and the evolution of cooperation

The structure of social interactions influences many aspects of social life, including the spread of information and behavior, and the evolution of social phenotypes. After dispersal, organisms move around throughout their lives, and the patterns of their movement influence their social encounters over the course of their lifespan. Though both space and mobility are known to influence social evolution, there is little analysis of the influence of specific movement patterns on evolutionary dynamics. We explored the effects of random movement strategies on the evolution of cooperation using an agent-based prisoner’s dilemma model with mobile agents. This is the first systematic analysis of a model in which cooperators and defectors can use different random movement strategies, which we chose to fall on a spectrum between highly exploratory and highly restricted in their search tendencies. Because limited dispersal and restrictions to local neighborhood size are known to influence the ability of cooperators to effectively assort, we also assessed the robustness of our findings with respect to dispersal and local capacity constraints. We show that differences in patterns of movement can dramatically influence the likelihood of cooperator success, and that the effects of different movement patterns are sensitive to environmental assumptions about offspring dispersal and local space constraints. Since local interactions implicitly generate dynamic social interaction networks, we also measured the average number of unique and total interactions over a lifetime and considered how these emergent network dynamics helped explain the results. This work extends what is known about mobility and the evolution of cooperation, and also has general implications for social models with randomly moving agents.     

Variation and the response to variation as a basis for successful cooperation

In applying game theory to problems in biology, differences between individuals are often ignored. In particular, when analysing the evolution of cooperation it is often implicitly assumed that ignoring variation will produce predictions that approximate the solution when differences are included. This need not be true. As we demonstrate, differences are not innocuous noise, but can fundamentally change the nature of a game. Even small amounts of variability can stabilize cooperation by, for example, maintaining the need to deal with cheaters. Differences promote the need to learn about others in an interaction, leading to contingent behaviour that can reduce conflict, and to negotiated outcomes that may or may not be more cooperative than unconditional actions. Once there are mechanisms such as mutation and environmental influences that maintain variation within populations, whether cooperation evolves may depend on the variation in the cooperativeness trait. Variation means that it may be worth taking a chance that a partner is cooperative by being cooperative. When there are markets, so that individuals can break off interactions to seek a better partner, variation promotes choosiness and hence penalizes those uncooperative individuals, who are rejected. Variation promotes the need to monitor the previous behaviour of others, and once this social sensitivity exists, the need to maintain a good reputation can promote cooperation.     

Working together may be better: activation of reward centers during a cooperative maze task

Humans use theory of mind when predicting the thoughts and feelings and actions of others. There is accumulating evidence that cooperation with a computerized game correlates with a unique pattern of brain activation. To investigate the neural correlates of cooperation in real-time we conducted an fMRI hyperscanning study. We hypothesized that real-time cooperation to complete a maze task, using a blind-driving paradigm, would activate substrates implicated in theory of mind. We also hypothesized that cooperation would activate neural reward centers more than when participants completed the maze themselves. Of interest and in support of our hypothesis we found left caudate and putamen activation when participants worked together to complete the maze. This suggests that cooperation during task completion is inherently rewarding. This finding represents one of the first discoveries of a proximate neural mechanism for group based interactions in real-time, which indirectly supports the social brain hypothesis.     

Models of cooperation based on the Prisoner's Dilemma and the Snowdrift game

Understanding the mechanisms that can lead to the evolution of cooperation through natural selection is a core problem in biology. Among the various attempts at constructing a theory of cooperation, game theory has played a central role. Here, we review models of cooperation that are based on two simple games: the Prisoner's Dilemma, and the Snowdrift game. Both games are two‐person games with two strategies, to cooperate and to defect, and both games are social dilemmas. In social dilemmas, cooperation is prone to exploitation by defectors, and the average payoff in populations at evolutionary equilibrium is lower than it would be in populations consisting of only cooperators. The difference between the games is that cooperation is not maintained in the Prisoner's Dilemma, but persists in the Snowdrift game at an intermediate frequency. As a consequence, insights gained from studying extensions of the two games differ substantially. We review the most salient results obtained from extensions such as iteration, spatial structure, continuously variable cooperative investments, and multi‐person interactions. Bridging the gap between theoretical and empirical research is one of the main challenges for future studies of cooperation, and we conclude by pointing out a number of promising natural systems in which the theory can be tested experimentally.     

Why cooperation is not running away

A growing number of experimental and theoretical studies show the importance of partner choice as a mechanism to promote the evolution of cooperation, especially in humans. In this paper, we focus on the question of the precise quantitative level of cooperation that should evolve under this mechanism. When individuals compete to be chosen by others, their level of investment in cooperation evolves towards higher values, a process called competitive altruism, or runaway cooperation. Using a classic adaptive dynamics model, we first show that when the cost of changing partner is low, this runaway process can lead to a profitless escalation of cooperation. In the extreme, when partner choice is entirely frictionless, cooperation even increases up to a level where its cost entirely cancels out its benefit. That is, at evolutionary equilibrium, individuals gain the same payoff than if they had not cooperated at all. Second, importing models from matching theory in economics we, however, show that when individuals can plastically modulate their choosiness in function of their own cooperation level, partner choice stops being a runaway competition to outbid others and becomes a competition to form the most optimal partnerships. In this case, when the cost of changing partner tends towards zero, partner choice leads to the evolution of the socially optimum level of cooperation. This last result could explain the observation that human cooperation seems to be often constrained by considerations of social efficiency.     

Runaway selection for cooperation and strict-and-severe punishment

Punishing defectors is an important means of stabilizing cooperation. When levels of cooperation and punishment are continuous, individuals must employ suitable social standards for defining defectors and for determining punishment levels. Here we investigate the evolution of a social reaction norm, or psychological response function, for determining the punishment level meted out by individuals in dependence on the cooperation level exhibited by their neighbors in a lattice-structured population. We find that (1) cooperation and punishment can undergo runaway selection, with evolution towards enhanced cooperation and an ever more demanding punishment reaction norm mutually reinforcing each other; (2) this mechanism works best when punishment is strict, so that ambiguities in defining defectors are small; (3) when the strictness of punishment can adapt jointly with the threshold and severity of punishment, evolution favors the strict-and-severe punishment of individuals who offer slightly less than average cooperation levels; (4) strict-and-severe punishment naturally evolves and leads to much enhanced cooperation when cooperation without punishment would be weak and neither cooperation nor punishment are too costly; and (5) such evolutionary dynamics enable the bootstrapping of cooperation and punishment, through which defectors who never punish gradually and steadily evolve into cooperators who punish those they define as defectors.