Social exchange and reciprocity: confusion or a heuristic?

We propose that a “social exchange heuristic” is as important as the cheater detection mechanism for attaining mutual cooperation in social exchange. The social exchange heuristic prompts people to perceive a mixed-motive situation, such as the Prisoner's Dilemma (PD), as an Assurance Game (AG) situation in which cooperation is a personally better choice than defection insofar as the partner is cooperating as well. We demonstrate the operation of the social exchange heuristic through a comparison of the ordinary one-shot, simultaneous PD with the one-shot, sequential PD. Participants in the current experiments, involving a total of 261 volunteers, committed a logical error in the direction of favoring mutual cooperation as the situation involved more serious consequences. This result strongly suggests the operation of a domain specific “bias” that encourages pursuit of mutual cooperation in social exchange.     

The evolution of altruism: Correlation,cost, and benefit

A simple and general criterion is derived for the evolution of altruism when individuals interact in pairs. It is argued that the treatment of this problem in kin selection theory and in game theory are special cases of this general criterion.My thanks to James Crow, Carter Denniston, Lee Dugarkin, David Wilson, and an anonymous referee of this journal for helpful discussion.     

A simple learning strategy that realizes robust cooperation better than Pavlov in Iterated Prisoners' Dilemma

Pavlov was proposed as a leading strategy for realizing cooperation because it dominates over a long period in evolutionary computer simulations of the Iterated Prisoners' Dilemma. However, our numerical calculations reveal that Pavlov and also any other cooperative strategy are not evolutionarily stable among all stochastic strategies with memory of only one previous move. We propose simple learning based on reinforcement. The learner changes its internal state, depending on an evaluation of whether the score in the previous round is larger than a critical value (aspiration level), which is genetically fixed. The current internal state decides the learner's move, but we found that the aspiration level determines its final behavior. The cooperative variant, having an intermediate aspiration level, is not an evolutionarily stable strategy (ESS) when evaluation is binary (good or bad). However, when the evaluation is quantified some cooperative variants can invade not only All-C, Tit-For-Tat (TFT), and Pavlov but also noncooperative variants with different aspiration levels. Moreover, they establish robust cooperation, which is evolutionarily stable against invasion by All-C, All-D, TFT, Pavlov, and noncooperative variants, and they receive a high score even when the error rate is high. Our results suggest that mutual cooperation can be maintained when players have a primitive learning ability. Received: June 23, 2000 / Accepted: October 1, 2000     

Evolutionary stability of first-order-information indirect reciprocity in sizable groups

Indirect reciprocity is considered as a key mechanism for explaining the evolution of cooperation in situations where the same individuals interact only a few times. Under indirect reciprocity, an individual who helps others gets returns indirectly from others who know her good reputation. Recently, many studies have discussed the effect of reputation criteria based only on the former actions of the others (first-order information) and of those based also on the former reputation of opponents of the others (second-order information) on the evolution of indirect reciprocity. In this study, we investigate the evolutionary stability of the indirectly reciprocal strategy (discriminating strategy: DIS), which cooperates only with opponents who have good reputations, in -person games where more than two individuals take part in a single group (interaction). We show that in n-person games, DIS is an evolutionarily stable strategy (ESS) even under the image-scoring reputation criterion, which is based only on first-order information and where cooperations (defections) are judged to be good (bad). This result is in contrast to that of 2-person games where DIS is not an ESS under reputation criteria based only on first-order information.     

Spatial invasion of cooperation

The evolutionary puzzle of cooperation describes situations where cooperators provide a fitness benefit to other individuals at some cost to themselves. Under Darwinian selection, the evolution of cooperation is a conundrum, whereas non-cooperation (or defection) is not. In the absence of supporting mechanisms, cooperators perform poorly and decrease in abundance. Evolutionary game theory provides a powerful mathematical framework to address the problem of cooperation using the prisoner's dilemma. One well-studied possibility to maintain cooperation is to consider structured populations, where each individual interacts only with a limited subset of the population. This enables cooperators to form clusters such that they are more likely to interact with other cooperators instead of being exploited by defectors. Here we present a detailed analysis of how a few cooperators invade and expand in a world of defectors. If the invasion succeeds, the expansion process takes place in two stages: first, cooperators and defectors quickly establish a local equilibrium and then they uniformly expand in space. The second stage provides good estimates for the global equilibrium frequencies of cooperators and defectors. Under hospitable conditions, cooperators typically form a single, ever growing cluster interspersed with specks of defectors, whereas under more hostile conditions, cooperators form isolated, compact clusters that minimize exploitation by defectors. We provide the first quantitative assessment of the way cooperators arrange in space during invasion and find that the macroscopic properties and the emerging spatial patterns reveal information about the characteristics of the underlying microscopic interactions.     

The effect of dispersal and neighbourhood in games of cooperation

The prisoner's dilemma (PD) and the snowdrift (SD) games are paradigmatic tools to investigate the origin of cooperation. Whereas spatial structure (e.g. nonrandom spatial distribution of strategies) present in the spatially explicit models facilitates the emergence of cooperation in the PD game, recent investigations have suggested that spatial structure can be unfavourable for cooperation in the SD game. The frequency of cooperators in a spatially explicit SD game can be lower than it would be in an infinitely large well-mixed population. However, the source of this effect cannot be identified with certainty as spatially explicit games differ from well-mixed games in two aspects: (i) they introduce spatial correlations, (ii) and limited neighbourhood. Here we extend earlier investigations to identify the source of this effect, and thus accordingly we study a spatially explicit version of the PD and SD games with varying degrees of dispersal and neighbourhood size. It was found that dispersal favours selfish individuals in both games. We calculated the frequency of cooperators at strong dispersal limit, which in concordance with the numerical results shows that it is the short range of interactions (i.e. limited neighbourhood) and not spatial correlations that decreases the frequency of cooperators in spatially explicit models of populations. Our results demonstrate that spatial correlations are always beneficial to cooperators in both the PD and SD games. We explain the opposite effect of dispersal and neighbourhood structure, and discuss the relevance of distinguishing the two effects in general.     

A stochastic model of evolutionary dynamics with deterministic large-population asymptotics

An evolutionary birth-death process is proposed as a model of evolutionary dynamics. Agents residing in a continuous spatial environment X, play a game G, with a continuous strategy set S, against other agents in the environment. The agents’ positions and strategies continuously change in response to other agents and to random effects. Agents spawn asexually at rates that depend on their current fitness, and agents die at rates that depend on their local population density. Agents’ individual evolutionary trajectories in X and S are governed by a system of stochastic ODEs. When the number of agents is large and distributed in a smooth density on (X,S), the collective dynamics of the entire population is governed by a certain (deterministic) PDE, which we call a fitness-diffusion equation.     

Evolution of cooperation in patchy habitat under patch decay and isolation

The spatial version of Prisoners Dilemma (PD) is studied, which incorporates habitat decay through change in the mortality parameter and habitat isolation through change in the colonization coefficient. We found four kinds of evolutionary results, which are affected profoundly by the elements of the payoff matrix and the ratio of the colonization coefficient to the mortality parameter: population extinction, a pure cooperator population, coexistence of cooperators and defectors, and a pure defector population. First, the parameter region of cooperation (pure cooperator and coexistence region) shrinks with an increase in the cooperative cost, and that of defection extends. The increase in cooperative reward makes the cooperative region extend and the defector region become small. Second, the cooperative reward can compensate for the extinction risk due to habitat destruction and allow a population to survive even if the colonization coefficient is smaller than the mortality parameter. Third, although habitat destruction (including decay and isolation) increase the extinction risk of a population, moderate external power can push the evolution of cooperation ahead of population extinction, and even make a completely cooperative world come into being. Finally, for certain values of elements of the payoff matrix, the population suffering habitat destruction can maintain a stable population size by regulating the frequencies of cooperators and defectors. This implies that the multi-behavior strategy within a population may be a mechanism to defend against the influences of a changing environment.     

A new formalization of a meta-game using the lambda calculus

This paper presents a new game system formalism. The system describes both strategies and a game master (who computes scores in a given game system) in terms of λ-calculus. This formalism revisits the prisoner's dilemma game, to discuss how meta-strategies emerge in this classical game, even without repetition. We have also examined the evolution of meta-strategies in λ formalism.     

A microbial modified prisoner's dilemma game: how frequency-dependent selection can lead to random phase variation

Random phase variation (RPV) is a control strategy in which the expression of a cell state or phenotype randomly alternates between discrete 'on' and 'off' states. Though this mode of control is common for bacterial virulence factors like pili and toxins, precise conditions under which RPV confers an advantage have not been well defined. In Part I of this study, we predicted that fluctuating environments select for RPV if transitions between different selective environments cannot be reliably sensed (J. Theor. Biol. (2005)). However, selective forces both inside and outside of human hosts are also likely to be frequency dependent in the sense that the fitnesses of some bacterial states are greatest when rare. Here we show that RPV at slow rates can provide a survival advantage in such a frequency-dependent environment by generating population heterogeneity, essentially mimicking a polymorphism. More surprisingly, RPV at a faster 'optimal' rate can shift the population composition toward an optimal growth rate that exceeds that possible for polymorphic populations, but this optimal strategy is not evolutionarily stable. The population would be most fit if all cells randomly phase varied at the optimal rate, but individual cells have a growth-rate incentive to defect (mutate) to other switching rates or non-phase variable phenotype expression, leading to an overall loss of fitness of the individual and the population. This scenario describes a modified Prisoner's Dilemma game (Evolution and the Theory of Games, Cambridge University Press, Cambridge, New York, 1982, viii, 224pp.; Nature 398 (6726) (1999) 367), with random phase variation at optimal switching rates serving as the cooperation strategy.