Distinctions among reciprocal altruism,kin selection,and cooperation and a model for the initial evolution of beneficent behavior

Reciprocal altruism is usually regarded as distinct from kin selection. However, because reciprocators are likely to establish long-term relations and to deliver most of their aid to other individuals genetically predisposed to reciprocation, most acts of reciprocal altruism should involve indirect increments to inclusive fitness, at least as regards alleles for reciprocation. Thus, as usually defined, reciprocal altruism is not clearly distinct from kin selection because both involve indirect increments to inclusive fitness. We propose a new definition for reciprocal altruism that makes the phenomenon distinct from kin selection and allows for reciprocation between nonrelatives in which current costs exceed future benefits returned to the reciprocal altruist. Cooperation and reciprocal altruism are often considered synonymous or different only in the timing of donating and receiving aid. We show, however, that there are other critical differences between reciprocal altruism and other forms of cooperation, most importantly, the latter often involve no clearly identifiable aid. We propose a four-category system to encompass the range of cooperative and beneficent behaviors that occur in nature (reciprocal altruism, pseudoreciprocity, simultaneous cooperation and by-product beneficence). Reciprocal altruism must involve aid that is returned to an original donor as a result of behavior that has a net cost to an original recipient. Our simplest category of cooperative/beneficent behavior, “by-product beneficence,” occurs when a selfish act also benefits another individual and requires no prior or subsequent interactions between the individuals involved. By-product beneficence may be the primitive state from which more complicated types of cooperative/beneficent behavior evolved. We show via simple models that by-product beneficence can allow for the initial increase of helping behavior in a completely unstructured population although the individuals showing such behavior pay all the costs while sharing the benefits with other individuals. Previous models that attempted to explain the initial increase of cooperative/beneficent behavior were much more complex and were based on the prisoner's dilemma, which does not accurately reflect most forms of cooperation and beneficence that occur in nature.     

Reciprocal altruism in birds: A critical review

Many proposed examples of reciprocal altruism are either misidentified or involve questionable assumptions concerning the costs and benefits accruing to the interactors. Waltz's (Am. Nat. 118: 588–592, 1981) definition of reciprocal altruism as an interaction in which “one individual aids another in anticipation that the recipient will return the favor benefiting the actor in the future” is not sufficiently restrictive: there must also be a direct fitness cost to the individual performing the original beneficent act that is less than the fitness benefit received when the act is reciprocated (again at a cost) by the second individual.Several recurring problems in identifying potential examples of reciprocal altruism are discussed, including the assumption that restraint is an act of altruism and the misclassification of “generational mutualisms,” in which individuals helping to raise young are “repaid” one generation later by the offspring they assisted in raising. No definite case of reciprocal altruism is currently known in birds, but examples in which this phenomenon may be involved include helping behavior in a few cooperative breeders and communal feeding in several taxa including gulls, jays, and juncos.     

Competitive altruism: from reciprocity to the handicap principle

Current work on cooperation is focused on the theory of reciprocal altruism. However, reciprocity is just one way of getting a return on an investment in altruism and is difficult to apply to many examples. Reciprocity theory addresses how animals respond dynamically to others so as to cooperate without being exploited. I discuss how introducing differences in individual generosity together with partner choice into models of reciprocity can lead to an escalation in altruistic behaviour. Individuals may compete for the most altruistic partners and non-altruists may become ostracized. I refer to this phenomenon as competitive altruism and propose that it can represent a move away from the dynamic responsiveness of reciprocity. Altruism may be rewarded in kind, but rewards may be indirectly accrued or may not involve the return of altruism at all, for example if altruists tend to be chosen as mates. This variety makes the idea of competitive altruism relevant to behaviours which cannot be explained by reciprocity. I consider whether altruism might act as a signal of quality, as proposed by the handicap principle. I suggest that altruistic acts could make particularly effective signals because of the inherent benefits to receivers. I consider how reciprocity and competitive altruism are related and how they may be distinguished.     

Effects of information and group structure on evolution of altruism: analysis of two-score model by covariance and contextual analyses

An altruistic individual has to gamble on cooperation to a stranger because it does not know whether the stranger is trustworthy before direct interaction. Nowak and Sigmund (Nature 393 (1998a) 573; J. Theor. Biol. 194 (1998b) 561) presented a new theoretical framework of indirect reciprocal altruism by image scoring game where all individuals are informed about a partner's behavior from its image score without direct interaction. Interestingly, in a simplified version of the image scoring game, the evolutionarily stability condition for altruism became a similar form of Hamilton's rule, i.e. inequality that the probability of getting correct information is more than the ratio of cost to benefit. Since the Hamilton's rule was derived by evolutionarily stable analysis, the evolutionary meaning of the probability of getting correct information has not been clearly examined in terms of kin and group selection. In this study, we applied covariance analysis to the two-score model for deriving the Hamilton's rule. We confirmed that the probability of getting correct information was proportional to the bias of altruistic interactions caused by using information about a partner's image score. The Hamilton's rule was dependent on the number of game bouts even though the information reduced the risk of cooperation to selfish one at the first encounter. In addition, we incorporated group structure to the two-score model to examine whether the probability of getting correct information affect selection for altruism by group selection. We calculated a Hamilton's rule of group selection by contextual analysis. Group selection is very effective when either the probability of getting correct information or that of future interaction, or both are low. The two Hamilton's rules derived by covariance and contextual analyses demonstrated the effects of information and group structure on the evolution of altruism. We inferred that information about a partner's behavior and group structure can produce flexible pathways for the evolution of altruism.     

Primate Nepotism: What is the Explanatory Value of Kin Selection?

Kin selection theory (KS) is widely invoked to account for the preferential treatment of kin—nepotism—in primate societies. Because this idea is so pervasive the role of KS is often unquestioned and optional mechanisms are often ignored. I first examine the potential role of some other nepotism-generating mechanisms by concentrating on the effect of the proximity correlate of matrilineal kinship. This correlate of kinship may bias the development of mutually selfish interactions among relatives—kin-biased mutualism—and that of reciprocally altruistic interactions—kin-biased reciprocal altruism—two mechanisms that have been given little weight compared to KS and whose impact on the evolution of nepotism is therefore unknown. However, these two options to KS cannot account for the existence of unilaterally altruistic interactions among kin, which provide, therefore, the best type of evidence to test KS. But such evidence is difficult to obtain because many behaviors considered altruistic may in fact be selfish, and because kin altruism is seldom unilateral; it is most often bilateral, as expected by reciprocal altruism theory. For these reasons, one should be extremely cautious before equating nepotism exclusively with KS. Next, I examine the predictions of KS regarding the deployment of altruism according to degree of kinship by considering, in addition to the variables of Hamilton's equation, the duration of behaviors, the size of kin classes and their differential availability. In general, altruism is expected to be allocated at a fairly constant rate among kin categories and to drop markedly past the degree of relatedness beyond which altruism is no more profitable. Very little data allow one to test conclusively this prediction, as well as some other significant predictions. Overall, there is ample evidence for the role of KS in shaping mother-offspring interactions in various areas. But the evidence for kin-selected altruism beyond the mother-offspring bond (r < 0.5), though qualitatively solid, is much less abundant. Kin altruism drops markedly beyond r = 0.25 (half-siblings and grandmother-grandoffspring dyads).     

WHEN HAWKS GIVE RISE TO DOVES: THE EVOLUTION AND TRANSITION OF ENFORCEMENT STRATEGIES

The question of how altruism can evolve despite its local disadvantage to selfishness has produced a wealth of theoretical and empirical research capturing the attention of scientists across disciplines for decades. One feature that has remained consistent through this outpouring of knowledge has been that researchers have looked to the altruists themselves for mechanisms by which altruism can curtail selfishness. An alternative perspective may be that just as altruists want to limit selfishness in the population, so may the selfish individuals themselves. These alternative perspectives have been most evident in the fairly recent development of enforcement strategies. Punishment can effectively limit selfishness in the population, but it is not free. Thus, when punishment evolves among altruists, the double costs of exploitation from cheaters and punishment make the evolution of punishment problematic. Here we show that punishment can more readily invade selfish populations when associated with selfishness, whereas altruistic punishers cannot. Thereafter, the establishment of altruism because of enforcement by selfish punishers provides the ideal invasion conditions for altruistic punishment, effectively creating a transition of punishment from selfishness to altruistic. Thus, from chaotic beginnings, a little hypocrisy may go a long way in the evolution and maintenance of altruism.     

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.     

Evolution of alliance in primates: A population genetic model

Alliance behaviors in anubis baboons, chimpanzees, Japanese monkeys, and rhesus monkeys are briefly described. Alliance differs from simple altruism or cooperation between 2 individuals in that a third conspecific individual, the common enemy, is adversely affected. Two models of alliance formation are considered, one in which support is given unilaterally and the other in which both parties can profit. It is assumed that the allies are equally related to each other and to the common enemy. Using a quantitative genetic model, conditions are derived for alliance behavior to be selectively advantageous. The models are applied to reciprocal altruism between adult male anubis baboons and manipulation by adult male chimpanzees. It is argued that reciprocally altruistic alliance in baboons as described is difficult to reconcile with theory.     

The evolution of cooperation and altruism--a general framework and a classification of models

One of the enduring puzzles in biology and the social sciences is the origin and persistence of intraspecific cooperation and altruism in humans and other species. Hundreds of theoretical models have been proposed and there is much confusion about the relationship between these models. To clarify the situation, we developed a synthetic conceptual framework that delineates the conditions necessary for the evolution of altruism and cooperation. We show that at least one of the four following conditions needs to be fulfilled: direct benefits to the focal individual performing a cooperative act; direct or indirect information allowing a better than random guess about whether a given individual will behave cooperatively in repeated reciprocal interactions; preferential interactions between related individuals; and genetic correlation between genes coding for altruism and phenotypic traits that can be identified. When one or more of these conditions are met, altruism or cooperation can evolve if the cost-to-benefit ratio of altruistic and cooperative acts is greater than a threshold value. The cost-to-benefit ratio can be altered by coercion, punishment and policing which therefore act as mechanisms facilitating the evolution of altruism and cooperation. All the models proposed so far are explicitly or implicitly built on these general principles, allowing us to classify them into four general categories.     

Selection for altruism through random drift in variable size populations

ABSTRACT: BACKGROUND: Altruistic behavior is defined as helping others at a cost to oneself and a lowered fitness. The lower fitness implies that altruists should be selected against, which is in contradiction with their widespread presence is nature. Present models of selection for altruism (kin or multilevel) show that altruistic behaviors can have 'hidden' advantages if the 'common good' produced by altruists is restricted to some related or unrelated groups. These models are mostly deterministic, or assume a frequency dependent fitness. RESULTS: Evolutionary dynamics is a competition between deterministic selection pressure and stochastic events due to random sampling from one generation to the next. We show here that an altruistic allele extending the carrying capacity of the habitat can win by increasing the random drift of "selfish" alleles. In other terms, the fixation probability of altruistic genes can be higher than those of a selfish ones, even though altruists have a smaller fitness. Moreover when populations are geographically structured, the altruists advantage can be highly amplified and the fixation probability of selfish genes can tend toward zero. The above results are obtained both by numerical and analytical calculations. Analytical results are obtained in the limit of large populations. CONCLUSIONS: The theory we present does not involve kin or multilevel selection, but is based on the existence of random drift in variable size populations. The model is a generalization of the original Fisher-Wright and Moran models where the carrying capacity depends on the number of altruists.     

Communication and collective action: language and the evolution of human cooperation

All social species face various “collective action problems” (CAPs) or “social dilemmas,” meaning problems in achieving cooperating when the best move from a selfish point of view yields an inferior collective outcome. Compared to most other species, humans are very good at solving these challenges, suggesting that something rather peculiar about human sociality facilitates collective action. This article proposes that language — the uniquely human faculty of symbolic communication — fundamentally alters the possibilities for collective action. I explore these issues using simple game-theoretic models and empirical evidence (both ethnographic and experimental). I review several standard mechanisms for the evolution of cooperation — mutualism, reciprocal altruism, indirect reciprocity and signaling — highlighting their limitations when it comes to explaining large-group cooperation, as well as the ways in which language helps overcome those limitations. Language facilitates complex coordination and is essential for establishing norms governing production efforts and distribution of collective goods that motivate people to cooperate voluntarily in large groups. Language also significantly lowers the cost of detecting and punishing “free riders,” thus greatly enhancing the scope and power of standard conditional reciprocity. In addition, symbolic communication encourages new forms of collectively beneficial displays and reputation management — what evolutionists often term “signaling” and “indirect reciprocity.” Thus, language reinforces existing forces that favor the evolution of cooperation, as well as creating new opportunities for collective action not available even to our closest primate relatives.     

Altruism and mental disorders

Data suggest that the theories of kin selection and reciprocal altruism are viable working models to explain altruistic behavior. It remains to be demonstrated if these models can explain the behavior of persons with mentaL disorders for whom altruistic behavior is reported to be reduced. This paper addresses this issue. Part I reviews proximate factors that are thought to influence both altruistic decision making and interindividual variation in altruistic behavior. The focus is on trait signaling by potential beneficiaries and the evaluation of signals and altruistic decision making by potential altruists. In Part II, points developed in Part I are combined with clinical and empirical findings to analyze data on personality disorders and dysthymic disorder. The analysis leads to three causal hypotheses: Reduced altruistic behavior may be an evolved strategy, a consequence of dysfunctional recognition systems or algorithms, and/or a secondary response to an increase in symptoms. Different disorders and features of disorders are explained by each hypothesis.     

Altruism among non-relatives: alternatives to the 'Prisoner's Dilemma'

Triver's model of reciprocal altruism, and its descendants based on the Prisoner's Dilemma model, have dominated thinking about cooperation and altruism between non-relatives. However, there are three alternative models of altruism directed to non-relatives. These models, which are not based on the Prisoner's Dilemma, may explain a variety of phenomena, from allogrooming among impala to helping by non-relatives in cooperatively breeding birds and mammals.     

Models of the evolution of altruism

There are two ways of calculating the spread of a gene for altruism. One, originally proposed by Hamilton, is to allow for the effects of the gene on the survival and reproduction of collateral relatives of the individual carrying it (i.e., “inclusive fitness”); this leads to the condition k > 1/r for the spread of the gene, where k is a benefit/cost ratio. The other is to count only the direct offspring of a carrier, but to allow for the altruistic acts performed toward the carrier by its relatives (“neighbour modulated fitness” or “personal fitness”). A recent personal fitness model (L. L. Cavalli Sforza and M. W. Feldman, 1978, Theor. Pop. Biol.14, 268–280) analyses parent-offspring and sib-sib altruism and concludes that k > 1/r is applicable only when fitness components are combined additively. The present paper analyses some simple models in which the phenotypic effects are carefully specified. It is concluded that it is sometimes, but not always, appropriate to combine fitness components additively. The relative roles of inclusive and personal fitness models are compared. The former have the virtue of being easier to think about in causal terms; and the latter of incorporating the evolution of altruism into the corpus of population genetics as an example of frequency-dependent selection.     

Selfishness and altruism can coexist when help is subject to diminishing returns

Altruism and selfishness are 30-50% heritable in man in both Western and non-Western populations. This genetically based variation in altruism and selfishness requires explanation. In non-human animals, altruism is generally directed towards relatives, and satisfies the condition known as Hamilton's rule. This nepotistic altruism evolves under natural selection only if the ratio of the benefit of receiving help to the cost of giving it exceeds a value that depends on the relatedness of the individuals involved. Standard analyses assume that the benefit provided by each individual is the same but it is plausible in some cases that as more individuals contribute, help is subject to diminishing returns. We analyse this situation using a single-locus two-allele model of selection in a diploid population with the altruistic allele dominant to the selfish allele. The analysis requires calculation of the relationship between the fitnesses of the genotypes and the frequencies of the genes. The fitnesses vary not only with the genotype of the individual but also with the distribution of phenotypes amongst the sibs of the individual and this depends on the genotypes of his parents. These calculations are not possible by direct fitness or ESS methods but are possible using population genetics. Our analysis shows that diminishing returns change the operation of natural selection and the outcome can now be a stable equilibrium between altruistic and selfish alleles rather than the elimination of one allele or the other. We thus provide a plausible genetic model of kin selection that leads to the stable coexistence in the same population of both altruistic and selfish individuals. This may explain reported genetic variation in altruism in man.     

Models for alarm call behaviour

The evolution of alarm call behaviour under individual selection is studied. Four mathematical models of increasing complexity are proposed and analysed. Theoretical conditions for the evolution of “selfish”, “mutualistic”, “altruistic” or “spiteful” alarm calls are established. The models indicate that the hypotheses of benefits of retaining group members or avoiding group detection are not sufficient to explain the evolution of alarm call behaviour, but serve as a complementary factor to facilitate its evolution in most cases. It is hypothesized that the evolution of alarm calls between non-kin should evolve probably when calls are mutualistic, mildly altruistic and there are beneficial group size effects against predation.     

Darwinian selection and “altruism”

Models are proposed for evolution at a single locus affecting altruistic behavior in which genotypic fitnesses are Darwinian and frequency (but not density) dependent. The fitnesses are composed, either in a multiplicative or an additive way, of factors which depend on the receipt and donation of altruistic behavior. The factors are determined from the matrices of conditional probabilities which describe the genotypes of relatives. Since selection occurs, these probabilities are in terms of genotype frequencies. The relationship between the risk to helper and benefit to recipient which allows altruism to evolve is shown to depend on the kinship coefficient between helper and helped, the particular fitness function proposed and the degree of dominance of the altruism. The commonly accepted criteria of W. D. Hamilton [J. Theor. Biol.7 (1964), 1–16, 17–52] apply only in the additive case. A second class of models of social cooperation independent of relationship and its evolutionary dynamics are discussed.     

On the relationship between evolutionary and psychological definitions of altruism and selfishness

I examine the relationship between evolutionary definitions of altruism that are based on fitness effects and psychological definitions that are based on the motives of the actor. I show that evolutionary altruism can be motivated by proximate mechanisms that are psychologically either altruistic or selfish. I also show that evolutionary definitions do rely upon motives as a metaphor in which the outcome of natural selection is compared to the decisions of a psychologically selfish (or altruistic) individual. Ignoring the precise nature of both psychological and evolutionary definitions has obscured many important issues, including the biological roots of psychological altruism.     

Learning and stabilization of altruistic behaviors in multi-agent systems by reciprocity

Optimization of performance in collective systems often requires altruism. The emergence and stabilization of altruistic behaviors are difficult to achieve because the agents incur a cost when behaving altruistically. In this paper, we propose a biologically inspired strategy to learn stable altruistic behaviors in artificial multi-agent systems, namely reciprocal altruism. This strategy in conjunction with learning capabilities make altruistic agents cooperate only between themselves, thus preventing their exploitation by selfish agents, if future benefits are greater than the current cost of altruistic acts. Our multi-agent system is made up of agents with a behavior-based architecture. Agents learn the most suitable cooperative strategy for different environments by means of a reinforcement learning algorithm. Each agent receives a reinforcement signal that only measures its individual performance. Simulation results show how the multi-agent system learns stable altruistic behaviors, so achieving optimal (or near-to-optimal) performances in unknown and changing environments. Received: 1 August 1997 / Accepted in revised form: 28 November 1997