Questioning the cultural evolution of altruism

The evolutionary foundations of helping among nonkin in humans have been the object of intense debates in the past decades. One thesis has had a prominent influence in this debate: the suggestion that genuine altruism, strictly defined as a form of help that comes at a net fitness cost for the benefactor, might have evolved owing to cultural transmission. The gene–culture coevolution literature is wont to claim that cultural evolution changes the selective pressures that normally act to limit the emergence of altruistic behaviours. This paper aims to recall, however, that cultural transmission yields altruism only to the extent that it relies on maladaptive mechanisms, such as conformist imitation and (in some cases) payoff‐biased transmission. This point is sometimes obscured in the literature by a confusion between genuine altruism, maladaptive by definition, and mutualistic forms of cooperation, that benefit all parties in the long run. Theories of cultural altruism do not lift the selective pressures weighing on strictly altruistic actions; they merely shift the burden of maladaptation from social cognition to cultural transmission.     

The robustness of altruism as an evolutionary strategy

Kin selection, reciprocity and group selection are widely regarded as evolutionary mechanisms capable of sustaining altruism among humans andother cooperative species. Our research indicates, however, that these mechanisms are only particular examples of a broader set of evolutionary possibilities.In this paper we present the results of a series of simple replicator simulations, run on variations of the 2–player prisoner's dilemma, designed to illustrate the wide range of scenarios under which altruism proves to be robust under evolutionary pressures. The set of mechanisms we explore is divided into four categories:correlation, group selection, imitation, and punishment. We argue that correlation is the core phenomenon at work in all four categories.     

Levels of selection, altruism, and primate behavior.

Altruistic behaviors seem anomalous from a traditional view of Darwinian natural selection, and evolutionary explanations for them have generated much discussion. The debate centers around four major explanations: classic individual-level selection, reciprocity and game theory, kin selection, and trait-group selection. The historical context and defining criteria of each model must be reviewed before its validity can be assessed. Of these proposed mechanisms, group selection historically has been the most controversial. Although the extent to which empirical data support group selection hypotheses is uncertain, there is evidence for group-level selection among avirulent virus strains and foraging ant queens. Researchers studying mammalian behavior, particularly primatologists, have largely dismissed models of group-level selection. Most discussion of altruism among primates has focused on differences in fitness among individuals within a single group, but students of altruistic behaviors exhibited by primates also need to investigate intergroup variation with respect to these behaviors. Various altruistic behaviors are likely to have evolved through different forms of selection, and each example of apparent altruism therefore needs to be evaluated separately.     

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.     

The evolutionary language game: an orthogonal approach

Evolutionary game dynamics have been proposed as a mathematical framework for the cultural evolution of language and more specifically the evolution of vocabulary. This article discusses a model that is mutually exclusive in its underlying principals with some previously suggested models. The model describes how individuals in a population culturally acquire a vocabulary by actively participating in the acquisition process instead of passively observing and communicate through peer-to-peer interactions instead of vertical parent-offspring relations. Concretely, a notion of social/cultural learning called the naming game is first abstracted using learning theory. This abstraction defines the required cultural transmission mechanism for an evolutionary process. Second, the derived transmission system is expressed in terms of the well-known selection-mutation model defined in the context of evolutionary dynamics. In this way, the analogy between social learning and evolution at the level of meaning-word associations is made explicit. Although only horizontal and oblique transmission structures will be considered, extensions to vertical structures over different genetic generations can easily be incorporated. We provide a number of simplified experiments to clarify our reasoning.     

Correlated pay-offs are key to cooperation

The general belief that cooperation and altruism in social groups result primarily from kin selection has recently been challenged, not least because results from cooperatively breeding insects and vertebrates have shown that groups may be composed mainly of non-relatives. This allows testing predictions of reciprocity theory without the confounding effect of relatedness. Here, we review complementary and alternative evolutionary mechanisms to kin selection theory and provide empirical examples of cooperative behaviour among unrelated individuals in a wide range of taxa. In particular, we focus on the different forms of reciprocity and on their underlying decision rules, asking about evolutionary stability, the conditions selecting for reciprocity and the factors constraining reciprocal cooperation. We find that neither the cognitive requirements of reciprocal cooperation nor the often sequential nature of interactions are insuperable stumbling blocks for the evolution of reciprocity. We argue that simple decision rules such as ‘help anyone if helped by someone’ should get more attention in future research, because empirical studies show that animals apply such rules, and theoretical models find that they can create stable levels of cooperation under a wide range of conditions. Owing to its simplicity, behaviour based on such a heuristic may in fact be ubiquitous. Finally, we argue that the evolution of exchange and trading of service and commodities among social partners needs greater scientific focus.     

The importance of mechanisms for the evolution of cooperation

Studies aimed at explaining the evolution of phenotypic traits have often solely focused on fitness considerations, ignoring underlying mechanisms. In recent years, there has been an increasing call for integrating mechanistic perspectives in evolutionary considerations, but it is not clear whether and how mechanisms affect the course and outcome of evolution. To study this, we compare four mechanistic implementations of two well-studied models for the evolution of cooperation, the Iterated Prisoner''s Dilemma (IPD) game and the Iterated Snowdrift (ISD) game. Behavioural strategies are either implemented by a 1 : 1 genotype–phenotype mapping or by a simple neural network. Moreover, we consider two different scenarios for the effect of mutations. The same set of strategies is feasible in all four implementations, but the probability that a given strategy arises owing to mutation is largely dependent on the behavioural and genetic architecture. Our individual-based simulations show that this has major implications for the evolutionary outcome. In the ISD, different evolutionarily stable strategies are predominant in the four implementations, while in the IPD each implementation creates a characteristic dynamical pattern. As a consequence, the evolved average level of cooperation is also strongly dependent on the underlying mechanism. We argue that our findings are of general relevance for the evolution of social behaviour, pleading for the integration of a mechanistic perspective in models of social evolution.     

Multilevel selection and the social transmission of behavior

Many evolutionary models assume that behaviors are caused directly by genes. An implication is that behavioral uniformity should be found only in groups that are genetically uniform. Yet, the members of human social groups often behave in a uniform fashion, despite the fact that they are genetically diverse. Behavioral uniformity can occur through a variety of psychological mechanisms and social processes, such as imitation, consensus decision making, or the imposition of social norms. We present a series of models in which genes code for social transmission rules, which in turn govern the behaviors that are adopted. Transmission rules can evolve in randomly formed groups that concentrate phenotypic variation at the between-group level, favoring the evolution of altruistic behaviors and other group-advantageous traits. In addition, a direct bias toward adopting altruistic behaviors can evolve. Our models begin to show how group selection can be a strong force in human evolution, despite the absence of extreme genetic variation among groups.     

From reciprocity to unconditional altruism through signalling benefits

Cooperation among genetically unrelated individuals is commonly explained by the potential for future reciprocity or by the risk of being punished by group members. However, unconditional altruism is more difficult to explain. We demonstrate that unconditional altruism can evolve as a costly signal of individual quality (i.e. a handicap) as a consequence of reciprocal altruism. This is because the emergent correlation between altruism and individual quality in reciprocity games can facilitate the use of altruism as a quality indicator in a much wider context, outside the reciprocity game, thus affecting its further evolution through signalling benefits. Our model, based on multitype evolutionary game theory shows that, when the additive signalling benefit of donating help exceeds the cost for only some individuals (of high-quality state) but not for others (of low-quality state), the population possesses an evolutionarily stable strategy (ESS) profile wherein high-quality individuals cooperate unconditionally while low-quality individuals defect or play tit-for-tat (TfT). Hence, as predicted by Zahavi's handicap model, signalling benefits of altruistic acts can establish a stable generosity by high-quality individuals that no longer depends on the probability of future reciprocation or punishment.     

A behavioral analysis of altruism

Altruistic acts have been defined, in economic terms, as “…costly acts that confer economic benefits on other individuals” (Fehr and Fischbacher, 2003). In multi-player, one-shot prisoner's dilemma games, a significant number of players behave altruistically; their behavior benefits each of the other players but is costly to them. We consider three potential explanations for such altruism. The first explanation, following a suggestion by the philosopher Derek Parfit, assumes that players devise a strategy to avoid being free-loaders—and that in the present case this strategy dictates cooperation. The second explanation says that cooperators reject the one-shot aspect of the game and behave so as to maximize reward over a series of choices extending beyond the present situation (even though reward is not maximized in the present case). This explanation assumes that people may learn to extend the boundaries of their selves socially (beyond their own skin) as well as temporally (beyond the present moment). We propose a learning mechanism for such behavior analogous to the biological, evolutionary mechanism of group selection. The third explanation assumes that people's altruism is based on a straightforward balancing of undiscounted costs to themselves against discounted benefits to others (social discounting). The three proposed explanations of altruism complement each other.     

Is the repeated prisoner's dilemma a good model of reciprocal altruism?

Axelrod and Hamilton (1981) used the repeated prisoner's dilemma game as a basis for their widely cited analysis of the evolution of reciprocal altruism. Recently, it has been argued that the repeated prisoner's dilemma is not a good model for this task. Some critics have argued that the single period prisoner's dilemma represents mutualistic rather than altruistic social interactions. Others have argued that reciprocal altruism requires that the opportunities for altruism occur sequentially, first one individual and then after some delay the other. Here I begin by arguing that the single period prisoner's dilemma game is consistent with the definition of altruism that is widely accepted in evolutionary biology. Then I present two modified versions of the repeated prisoner's dilemma, one in which behavior is sequential, and a second in which behavior occurs in continuous time. Each of these models shares the essential qualitative properties with the version used by Axelrod and Hamilton.     

The behavioural ecology of personality: consistent individual differences from an adaptive perspective

Individual humans, and members of diverse other species, show consistent differences in aggressiveness, shyness, sociability and activity. Such intraspecific differences in behaviour have been widely assumed to be non‐adaptive variation surrounding (possibly) adaptive population‐average behaviour. Nevertheless, in keeping with recent calls to apply Darwinian reasoning to ever‐finer scales of biological variation, we sketch the fundamentals of an adaptive theory of consistent individual differences in behaviour. Our thesis is based on the notion that such ‘personality differences’ can be selected for if fitness payoffs are dependent on both the frequencies with which competing strategies are played and an individual's behavioural history. To this end, we review existing models that illustrate this and propose a game theoretic approach to analyzing personality differences that is both dynamic and state‐dependent. Our motivation is to provide insights into the evolution and maintenance of an apparently common animal trait: personality, which has far reaching ecological and evolutionary implications.     

The evolution of altruism: game theory in multilevel selection and inclusive fitness

Although the prisoner's dilemma (PD) has been used extensively to study reciprocal altruism, here we show that the n-player prisoner's dilemma (NPD) is also central to two other prominent theories of the evolution of altruism: inclusive fitness and multilevel selection. An NPD model captures the essential factors for the evolution of altruism directly in its parameters and integrates important aspects of these two theories such as Hamilton's rule, Simpson's paradox, and the Price covariance equation. The model also suggests a simple interpretation of the Price selection decomposition and an alternative decomposition that is symmetrical and complementary to it. In some situations this alternative shows the temporal changes in within- and between-group selection more clearly than the Price equation. In addition, we provide a new perspective on strong vs. weak altruism by identifying their different underlying game structures (based on absolute fitness) and showing how their evolutionary dynamics are nevertheless similar under selection (based on relative fitness). In contrast to conventional wisdom, the model shows that both strong and weak altruism can evolve in periodically formed random groups of non-conditional strategies if groups are multigenerational. An integrative approach based on the NPD helps unify different perspectives on the evolution of altruism.     

A game theoretical approach to the evolution of structured communication codes

Structured meaning-signal mappings, i.e., mappings that preserve neighborhood relationships by associating similar signals with similar meanings, are advantageous in an environment where signals are corrupted by noise and sub-optimal meaning inferences are rewarded as well. The evolution of these mappings, however, cannot be explained within a traditional language evolutionary game scenario in which individuals meet randomly because the evolutionary dynamics is trapped in local maxima that do not reflect the structure of the meaning and signal spaces. Here we use a simple game theoretical model to show analytically that when individuals adopting the same communication code meet more frequently than individuals using different codes—a result of the spatial organization of the population—then advantageous linguistic innovations can spread and take over the population. In addition, we report results of simulations in which an individual can communicate only with its K nearest neighbors and show that the probability that the lineage of a mutant that uses a more efficient communication code becomes fixed decreases exponentially with increasing K. These findings support the mother tongue hypothesis that human language evolved as a communication system used among kin, especially between mothers and offspring.     

Group beneficial norms can spread rapidly in a structured population

Group beneficial norms are common in human societies. The persistence of such norms is consistent with evolutionary game theory, but existing models do not provide a plausible explanation for why they are common. We show that when a model of imitation used to derive replicator dynamics in isolated populations is generalized to allow for population structure, group beneficial norms can spread rapidly under plausible conditions. We also show that this mechanism allows recombination of different group beneficial norms arising in different populations.     

Acceptor control in model ecosystems

The analysis of models of evolutionary games requires explicit consideration of both evolutionary game rules and mutants which infinitesimally break these rules. For example, the Scotch Auction is an evolutionary game which lacks both a rule-obeying evolutionarily stable strategy and an asymptotically stable polymorphism of rule-obeying strategies. However, an infinitesimal rule-breaking, or cheating, mutant can be found which is an evolutionarily stable strategy against rule-obeying strategies. Such cheating strategies can spread through populations initially playing the Scotch Auction, effectively changing the rules of the game. Moreover, the extent of such rule-change will then tend to increase. Thus, the Scotch Auction is a transient evolutionary game, being the initial point of a seemingly orthogenetic game evolutionary process. This sort of transience suggests that the “progressive” nature of evolution may be due in part to those game features of evolutionary processes which make the success of adaptations relative to the level of extant adaptation among competitors, predators, etc.     

Asymmetric Evolutionary Games

Evolutionary game theory is a powerful framework for studying evolution in populations of interacting individuals. A common assumption in evolutionary game theory is that interactions are symmetric, which means that the players are distinguished by only their strategies. In nature, however, the microscopic interactions between players are nearly always asymmetric due to environmental effects, differing baseline characteristics, and other possible sources of heterogeneity. To model these phenomena, we introduce into evolutionary game theory two broad classes of asymmetric interactions: ecological and genotypic. Ecological asymmetry results from variation in the environments of the players, while genotypic asymmetry is a consequence of the players having differing baseline genotypes. We develop a theory of these forms of asymmetry for games in structured populations and use the classical social dilemmas, the Prisoner’s Dilemma and the Snowdrift Game, for illustrations. Interestingly, asymmetric games reveal essential differences between models of genetic evolution based on reproduction and models of cultural evolution based on imitation that are not apparent in symmetric games.     

Fairness evolution in the ultimatum game is a function of reward size

I formulate a simple model of the ultimatum game, in which a proposer and a responder can receive a reward if they agree on how to divide this reward between them. The model is easy to analyse and shows that strong tendencies to fair division are expected when evolution of strategy frequencies follow the traditional gradient dynamics assumed in evolutionary models. The mean stable offer is typically around 20-40% although this depends on the maximum payoff and if rejection thresholds can evolve independently from proposals. The stable proportion offered at evolutionary equilibrium increases with the maximum payoff, if proposal and acceptance thresholds are dictated by the same strategy and cannot evolve independently. If proposal and acceptance evolve independently, the stable proportion instead decreases with the maximum payoff. The stable outcome may also show substantial variation.     

The continuous public goods game and the evolution of cooperative sex ratios

Some animals, such as Melittobia wasps and surface-living mites, have extremely female-biased sex ratios that cannot be explained by the existing local mate competition (LMC) theories. The restricted production of sons may entail cooperation among mothers, enabling the production of more daughters and avoiding severe competition among sons for insemination access. These unusual examples are characterized by the long-term cohabitation of egg-layers (foundresses) on resource patches and possible contact with oviposited eggs. By applying the logic of mutual policing, we develop a novel game theoretical model for the evolution of cooperation in sex-ratio traits. This is the first attempt to model the evolution of sex ratios based on iterated games. We assumed that foundresses have two abilities to enable mutual policing: they can monitor the sex ratio in the resource patch, and they can punish defectors that produce an overabundance of males. Numerical analysis and evolutionary simulations demonstrate that cooperative low sex ratios can evolve when the number of foundresses per patch is sufficiently small. Our model predicts a slight, but steady increase in oviposition sex ratios with an increase in the number of foundresses, which mimics the phenomenon observed in several animals with extremely female-biased sex ratios. We also discuss the relationship between our model and other models of sex-ratio evolution.     

MATHEMATICS OF KIN‐ AND GROUP‐SELECTION: FORMALLY EQUIVALENT?

Evolutionary game theory is a general mathematical framework that describes the evolution of social traits. This framework forms the basis of many multilevel selection models and is also frequently used to model evolutionary dynamics on networks. Kin selection, which was initially restricted to describe social interactions between relatives, has also led to a broader mathematical approach, inclusive fitness, that can not only describe social evolution among relatives, but also in group structured populations or on social networks. It turns out that the underlying mathematics of game theory is fundamentally different from the approach of inclusive fitness. Thus, both approaches—evolutionary game theory and inclusive fitness—can be helpful to understand the evolution of social traits in group structured or spatially extended populations.