Evolution Of Cooperative Behavior Research Articles

Contributions of genetic and nongenetic sources to variation in cooperative behavior in a cooperative mammal.

The evolution of cooperative behavior is a major area of research among evolutionary biologists and behavioral ecologists, yet there are few estimates of its heritability or its evolutionary potential, and long-term studies of identifiable individuals are required to disentangle genetic and nongenetic components of cooperative behavior. Here, we use long-term data on over 1800 individually recognizable wild meerkats (Suricata suricatta) collected over 30 years and a multigenerational genetic pedigree to partition phenotypic variation in three cooperative behaviors (babysitting, pup feeding, and sentinel behavior) into individual, additive genetic, and other sources, and to assess their repeatability and heritability. In addition to strong effects of sex, age, and dominance status, we found significant repeatability in individual contributions to all three types of cooperative behavior both within and across breeding seasons. Like most other studies of the heritability of social behavior, we found that the heritability of cooperative behavior was low. However, our analysis suggests that a substantial component of the repeatable individual differences in cooperative behavior that we observed was a consequence of additive genetic variation. Our results consequently indicate that cooperative behavior can respond to selection, and suggest scope for further exploration of the genetic basis of social behavior.

On the importance of defendable resources for social evolution: Applying new techniques to a long‐standing question

AbstractCooperative behaviour often co‐occurs with the defence of key resources, typically in the form of a breeding site or territory communally exploited by a group of cooperating individuals. Nevertheless, not all animals that defend resources evolve advanced forms of cooperation and sociality—many non‐cooperative species occupy resources that do not differ in obvious ways from those inhabited by cooperative species. A key question is thus whether cooperation confers more subtle benefits, for example by allowing access to higher quality resources through competitive exclusion of less social rivals. In other words, it is not clear whether defendable resources are a necessary precondition for sociality or whether they also contribute to the maintenance and enhancement of cooperative societies. Here, we highlight how advances in imaging technology, machine‐learning, and environmental reconstruction enable the collection of behavioural and ecological data in unparalleled quantity and quality to address this question. These new techniques are especially suited to compare small‐scale differences in resource use between cooperative and non‐cooperative species that share a general habitat and have similar ecologies. The lamprologine cichlids of Lake Tanganyika are a prominent example of such a system and Michael Taborsky's pioneering work on this group has done much to promote these fishes as models of social evolution. We show that habitat features indicative of increased resource quality, namely increased stone cover, are indeed associated with the distribution of cooperative cichlids—at least where these resources are relatively scarce. We thus support a point Michael Taborsky made in 1981: the evolution of cooperative behaviour among cichlids is tied to their close association with a crucial resource, the substrate in which they hide and breed. In the future, the techniques we introduce here will allow to also investigate whether this substrate is indeed more than just the necessary precondition for cooperation among fishes; in addition, they will likely find application in a wide range of research fields interested in the interplay between biotic and abiotic environmental factors.

Increases in glucocorticoids are sufficient but not necessary to increase cooperative burrowing in Damaraland mole-rats

Despite widespread interest in the evolution of cooperative behaviour, the physiological mechanisms shaping their expression remain elusive. We tested the hypothesis that glucocorticoid (GC) hormones affect cooperative behaviour using captive Damaraland mole-rats (Fukomys damarensis), a cooperatively breeding mammal. Within groups, individuals routinely contribute to public goods that include foraging tunnels, which provide all group members access to the tubers of desert plants they feed on, communal food stores and nests. We found that experimental increases in glucocorticoid concentration (GCc) in non-breeding female helpers led them to be active for longer and to burrow more while active, raising their daily contributions to burrowing, but not food carrying or nest building. However, experimentally induced increases in burrowing did not lead to elevated GCc in helpers of both sexes. These results suggest that heightened GCc may stimulate some cooperative behaviours that are energetically demanding (a characteristic shared by many types of cooperative activities across species) but that the cooperative behaviours affected by GCc can also be regulated by other mechanisms.

Prosociality, social tolerance and partner choice facilitate mutually beneficial cooperation in common marmosets, Callithrix jacchus

Prosocial motivation has been suggested to facilitate the initiation and maintenance of cooperative interactions, as well as the evolution of social systems reliant on helping behaviour and social coordination. Previous comparative research on the link between prosociality and cooperation has been limited, however, by the absence of directly comparable measures of these traits among the same individuals. In the present study, we therefore examined intraspecific variation in prosociality and cooperative behaviour within a captive colony of group-living, cooperatively breeding common marmosets to provide a direct experimental test of these hypothesized benefits. We measured prosociality using a group service food-provisioning paradigm, and we assessed mutually beneficial dyadic cooperation with the loose string coordinated pulling paradigm. In addition, we also investigated the effects of individual social tolerance and partner choice, which have previously been identified as key factors promoting prosociality and cooperation among primates. As predicted, successful cooperation in the loose string paradigm was positively associated with prosociality, as well as with social tolerance and partner choice. These effects were independent of age, sex, personality, food motivation and learning across experimental sessions. Our results therefore suggest that prosocial motivation, social tolerance and partner choice can each facilitate mutually beneficial cooperation and social coordination in marmosets, supporting the hypothesized role of these mechanisms in the evolution of cooperative behaviour among primates.

Stable leaders pave the way for cooperation under time-dependent exploration rates.

The exploration of different behaviours is part of the adaptation repertoire of individuals to new environments. Here, we explore how the evolution of cooperative behaviour is affected by the interplay between exploration dynamics and social learning, in particular when individuals engage on prisoner’s dilemma along the edges of a social network. We show that when the population undergoes a transition from strong to weak exploration rates a decline in the overall levels of cooperation is observed. However, if the rate of decay is lower in highly connected individuals (Leaders) than for the less connected individuals (Followers) then the population is able to achieve higher levels of cooperation. Finally, we show that minor differences in selection intensities (the degree of determinism in social learning) and individual exploration rates, can translate into major differences in the observed collective dynamics.

Information exchange promotes and jeopardizes cooperation on interdependent networks

Information exchange has a significant influence on human behaviour decision-making. To explore the impact of the information exchange mechanism on the evolution of cooperative behaviour on the complex networks, we establish two-layer interdependent networks. Individuals have a certain probability of having information exchange with individuals on another network. In detail, when individuals residing on different networks are connected by links, the update of strategies not only depends on their own payoffs, but also depends on the strategy selections of the corresponding nodes and neighbours on the other network. Numerous simulations reveal that high cooperation level can be achieved for a large coupling probability and intermediate heterogeneity. Counter-intuitively, cooperation is not always promoted by the expansion of information sources. Our study thus enhances the understanding of the evolution of cooperation on interdependent networks.

Evolutionary Optimization of Cooperative Strategies for the Iterated Prisoner's Dilemma

The iterated prisoner's dilemma (IPD) has been studied in fields as diverse as economics, computer science, psychology, politics, and environmental studies. This is due, in part, to the intriguing property that its Nash equilibrium is not globally optimal. Typically treated as a single-objective problem, a player's goal is to maximize their own score. In some work, minimizing the opponent's score is an additional objective. In this article, we explore the role of explicitly optimizing for mutual cooperation in IPD player performance. We implement a genetic algorithm in which each member of the population evolves using one of four multiobjective fitness functions: selfish, communal, cooperative, and selfless, the last three of which use a cooperative metric as an objective. As a control, we also consider two single-objective fitness functions. We explore the role of representation in evolving cooperation by implementing four representations for evolving players. Finally, we evaluate the effect of noise on the evolution of cooperative behaviors. Testing our evolved players in tournaments in which a player's own score is the sole metric, we find that players evolved with mutual cooperation as an objective are very competitive. Thus, learning to play nicely with others is a successful strategy for maximizing personal reward.

Commodity-specific punishment for experimentally induced defection in cooperatively breeding fish.

Coercion is an important but underrated component in the evolution of cooperative behaviour. According to the pay-to-stay hypothesis of cooperative breeding, subordinates trade alloparental care for the concession to stay in the group. Punishment of idle subordinates is a key prediction of this hypothesis, which has received some experimental scrutiny. However, previous studies neither allowed separating between punishment and effects of disruption of social dynamics, nor did they differentiate between different helping behaviours that may reflect either mutualistic or reciprocal interaction dynamics. In the cooperative breeder Neolamprologus pulcher, we experimentally engineered the ability of subordinates to contribute to alloparental care by manipulating two different helping behaviours independently from one another in a full factorial design. We recorded the treatment effects on breeder aggression, subordinate helping efforts and submissive displays. We found two divergent regulatory mechanisms of cooperation, dependent on behavioural function. Experimental impediment of territory maintenance of subordinates triggered punishment by dominants, whereas prevented defence against egg predators released a compensatory response of subordinates without any enforcement, suggesting pre-emptive appeasement. These effects occurred independently of one another. Apparently, in the complex negotiation process among members of cooperative groups, behaviours fulfilling different functions may be regulated by divergent interaction mechanisms.

Individual diversity between interdependent networks promotes the evolution of cooperation by means of mixed coupling

Along with the rapid development of network-based information technology, such as cloud computing, big data, the IoT, and so on, human society has stepped into a new era of complex networks. People’s life and production activities depend more and more on various complex networks to ensure security and reliability. The complex interrelationships between human and nature establish a link to explain the cooperation of individual behaviour, especially for individual diversity. However, existing researches mostly ignore the influence of individual diversity on networks involved in individual behaviour to strategy selection. Therefore, it needs further research on how to consider both individual diversity and independent networks in the evolution of cooperative behaviour. To address this issue, we extend a simple game model into the interdependent networks through the mixed coupling (i.e., utility and probability) in this work. Also, we divide the kinds of strategic behaviour of a player in one layer concerning individual diversity. Moreover, there exists an optimal region of mixed coupling between networks such that cooperation can be promoted. Finally, experimental results can open the path to understanding the emergence and maintenance of cooperation within various interconnected and interrelated real-world systems newly.

Bacterial Cheaters Evade Punishment by Cyanide.

SummaryIn all domains of life, mechanisms exist that protect cooperating groups from exploitation by cheaters. Recent observations with the bacterium Pseudomonas aeruginosa have suggested a paradigmatic cheater control mechanism in which cooperator cells punish or “police” cheater cells by cyanide poisoning. These cheater cells are deficient in a pleiotropic quorum-sensing regulator that controls the production of cooperative secretions including cyanide, and presumably also cyanide resistance. In this study, we directly tested and refuted the cyanide policing model. Contrary to the hypothesis, cheater fitness was unaffected by the presence of cyanide. Cheater mutants grew equally well in co-cultures with either cyanide-proficient or cyanide-deficient cooperators, and they were as resistant to exogenous cyanide as wild-type cells. We show that these behaviors are the result of quorum-sensing-independent and cyanide-responsive resistance gene regulation. Our results highlight the role of genetic architecture in the evolution of cooperative behavior.

Parent-preferred dispersal promotes cooperation in structured populations.

Dispersal is a key process for the emergence of social and biological behaviours. Yet, little attention has been paid to dispersal's effects on the evolution of cooperative behaviour in structured populations. To address this issue, we propose two new dispersal modes, parent-preferred and offspring-preferred dispersal, incorporate them into the birth-death update rule, and consider the resultant strategy evolution in the prisoner's dilemma on random-regular, small-world, and scale-free networks, respectively. We find that parent-preferred dispersal favours the evolution of cooperation in these different types of population structures, while offspring-preferred dispersal inhibits the evolution of cooperation in homogeneous populations. On scale-free networks when the strength of parent-preferred dispersal is weak, cooperation can be enhanced at intermediate strengths of offspring-preferred dispersal, and cooperators can coexist with defectors at high strengths of offspring-preferred dispersal. Moreover, our theoretical analysis based on the pair-approximation method corroborates the evolutionary outcomes on random-regular networks. We also incorporate the two new dispersal modes into three other update rules (death-birth, imitation, and pairwise comparison updating), and find that similar results about the effects of parent-preferred and offspring-preferred dispersal can again be observed in the aforementioned different types of population structures. Our work, thus, unveils robust effects of preferential dispersal modes on the evolution of cooperation in different interactive environments.

A review on animal-robot interaction: from bio-hybrid organisms to mixed societies.

Living organisms are far superior to state-of-the-art robots as they have evolved a wide number of capabilities that far encompass our most advanced technologies. The merging of biological and artificial world, both physically and cognitively, represents a new trend in robotics that provides promising prospects to revolutionize the paradigms of conventional bio-inspired design as well as biological research. In this review, a comprehensive definition of animal-robot interactive technologies is given. They can be at animal level, by augmenting physical or mental capabilities through an integrated technology, or at group level, in which real animals interact with robotic conspecifics. Furthermore, an overview of the current state of the art and the recent trends in this novel context is provided. Bio-hybrid organisms represent a promising research area allowing us to understand how a biological apparatus (e.g. muscular and/or neural) works, thanks to the interaction with the integrated technologies. Furthermore, by using artificial agents, it is possible to shed light on social behaviours characterizing mixed societies. The robots can be used to manipulate groups of living organisms to understand self-organization and the evolution of cooperative behaviour and communication.

On the Spatial Diffusion of Cooperation with Endogenous Matching Institutions

This paper studies the spatial joint evolution of cooperative behavior and a partially assortative matching institution that protects cooperators. We consider cooperation as characterized by a cultural trait transmitted via an endogenous socialization mechanism and we assume that such trait can diffuse randomly in space due to some spatial noise in the socialization mechanism. Using mathematical techniques from reaction-diffusion equations theory, we show that, under some conditions, an initially localized domain of preferences for cooperation can invade the whole population and characterize the asymptotic speed of diffusion. We consider first the case with exogenous assortativeness, and then endogeneize the degree of social segmentation in matching, assuming that it is collectively set at each point of time and space by the local community. We show how relatively low cost segmenting institutions can appear in new places thanks to the spatial random diffusion of cooperation, helping a localized cultural cluster of cooperation to invade the whole population. The endogenous assortative matching institution follows a life cycle process: appearing, growing and then disappearing once a culture of cooperation is sufficiently established in the local population.

How much cost should reciprocators pay in order to distinguish the opponent's cooperation from the opponent's defection?

Reciprocity is a potential mechanism that encourages the evolution of cooperation. We consider the case where reciprocators’ cognitive ability of distinguishing the opponent's cooperation from the opponent's defection imposes a recognition cost. While it is natural to consider how recognition accuracy depends upon the magnitude of the recognition cost, it is rather unclear which amounts of the recognition cost paid by the reciprocator are most likely to evolve. By using the evolutionarily stable strategy analysis, we herein tackle this problem and show that the condition under which reciprocators can resist the invasion of unconditional defectors is most relaxed when they have perfect perception. We further consider a game with three strategies played by unconditional defectors and two types of heterogeneous reciprocators with different perceptual abilities. Our analysis shows that only when execution error rates are large enough, it is possible for reciprocators with lower perceptual ability to resist the invasion of both the unconditional defectors and reciprocators with higher perceptual abilities. These findings advance our understanding of the evolution of perception and its eminent role in the evolution of cooperative behavior.

The Impact of Multidrive on the Cooperation in N-person Snowdrift Game

This paper focuses on the N-person Snowdrift Game with double thresholds in the well-mixed population. By means of modeling and numerical simulation, we found that the double thresholds have important influence on the evolution of cooperative behavior, and polarize cooperative behavior in the end. There is a transformation point of the gap between the double thresholds. When the gap is lower than the transformation point, there is only one stable solution. As the gap raising, another stable solution with low cooperation level will appear. Furthermore, with the increasing of the gap, the transfer rate of defector to cooperator decreases. These results have theoretical guidance for the project management of modern enterprises.

3D model for optimising the communication topologies of iterated N-players prisoners' dilemma

The evolution of cooperative behaviour in iterated N-players prisoners' dilemma (INPPD) is studied over several communication topologies. Existing models presented several solution models for evolving the cooperative behaviour among INPPD players. The researches revealed that none of the existing models pay attention to the pivot role of the best players in evolving the cooperative behaviour. In this paper, we present a 3D model for optimising communication topologies of INPPD to increase the cooperative rate between players. The 3D model aims to transfer well-known topologies to new 3D topologies that give the best players major roles in the game. This is important as exchanging experiences between players is essential for evolving effective cooperation. Concerning the evolutionary algorithm, this model was designed with the support of a genetic algorithm with synchronous updating to evolve the players' strategies. The results showed that the 3D model could increase the cooperative rate dramatically when compared to the original communication topologies.

3D Model for Optimizing the Communication Topologies of Iterated N-Players Prisoners

The evolution of cooperative behaviour in iterated N-players prisoners' dilemma (INPPD) is studied over several communication topologies. Existing models presented several solution models for evolving the cooperative behaviour among INPPD players. The researches revealed that none of the existing models pay attention to the pivot role of the best players in evolving the cooperative behaviour. In this paper, we present a 3D model for optimising communication topologies of INPPD to increase the cooperative rate between players. The 3D model aims to transfer well-known topologies to new 3D topologies that give the best players major roles in the game. This is important as exchanging experiences between players is essential for evolving effective cooperation. Concerning the evolutionary algorithm, this model was designed with the support of a genetic algorithm with synchronous updating to evolve the players' strategies. The results showed that the 3D model could increase the cooperative rate dramatically when compared to the original communication topologies.

The influence of migration speed on cooperation in spatial games

Migration is a common phenomenon in human society which provides a person an opportunity to search for a new life from one area to another. In the framework of game theory, people may migrate to escape from a current adverse environment (evading defection). Since people may migrate at different speeds, it is interesting to figure out the influence of migration speed on the evolution of cooperative behavior. In an attempt to discover the influence, we propose here a model based on an adaptive migration mechanism. In this model, an individual migrates or updates his/her strategy asynchronously, which is tuned by migration frequency. Firstly, it is found that an appropriate migration speed may evoke an effective mechanism, which enables cooperators dominate even in highly adverse conditions. Secondly, we check how migration speed alters the paradigm of cooperation quantitatively in the conditions of different migration frequency. When migration frequency is high, cooperation is promoted only at a small migration speed. However, when migration frequency is low, cooperation is always promoted at any migration speed. In addition, we also investigated the influence of temptation to defect on cooperation for the case of different migration speeds and migration frequencies. Our results may provide a fresh perspective on the understanding of how human behavior affects cooperation.

Impact of strategy-neutral rewarding on the evolution of cooperative behavior

Social rewarding is a common but significant mechanism that promotes the evolution of cooperation. However, besides social rewarding, antisocial rewarding is also ordinary. Thus, we study the evolution of cooperation on prison dilemma game with strategy-neutral rewarding, namely a mechanism including social and antisocial rewarding. Two additional strategies, rewarding cooperators (RC) and rewarding defectors (RD), which establish union-like support to aid akin players are introduced. We show that the new mechanism greatly promotes the evolution of cooperation even in the presence of antisocial rewarding. The rewarding cooperators can enjoy both the benefits of their prosocial contributions and the corresponding rewards, thus they can form cooperative clusters to resist the aggression of defectors. On the other hand, due to their inherent greedy, rewarding defectors fail to secure a sustainable future. Our research might provide valuable insights into further exploring the nature of cooperation in the real world.

Intermediate Levels of Network Heterogeneity Provide the Best Evolutionary Outcomes

Complex networks impact the diffusion of ideas and innovations, the formation of opinions, and the evolution of cooperative behavior. In this context, heterogeneous structures have been shown to generate a coordination-like dynamics that drives a population towards a monomorphic state. In contrast, homogeneous networks tend to result in a stable co-existence of multiple traits in the population. These conclusions have been reached through the analysis of networks with either very high or very low levels of degree heterogeneity. In this paper, we use methods from Evolutionary Game Theory to explore how different levels of degree heterogeneity impact the fate of cooperation in structured populations whose individuals face the Prisoner’s Dilemma. Our results suggest that in large networks a minimum level of heterogeneity is necessary for a society to become evolutionary viable. Moreover, there is an optimal range of heterogeneity levels that maximize the resilience of the society facing an increasing number of social dilemmas. Finally, as the level of degree heterogeneity increases, the evolutionary dominance of either cooperators or defectors in a society increasingly depends on the initial state of a few influential individuals. Our findings imply that neither very unequal nor very equal societies offer the best evolutionary outcome.