Universal scaling for the dilemma strength in evolutionary games

Why would natural selection favor the prevalence of cooperation within the groups of selfish individuals? A fruitful framework to address this question is evolutionary game theory, the essence of which is captured in the so-called social dilemmas. Such dilemmas have sparked the development of a variety of mathematical approaches to assess the conditions under which cooperation evolves. Furthermore, borrowing from statistical physics and network science, the research of the evolutionary game dynamics has been enriched with phenomena such as pattern formation, equilibrium selection, and self-organization. Numerous advances in understanding the evolution of cooperative behavior over the last few decades have recently been distilled into five reciprocity mechanisms: direct reciprocity, indirect reciprocity, kin selection, group selection, and network reciprocity. However, when social viscosity is introduced into a population via any of the reciprocity mechanisms, the existing scaling parameters for the dilemma strength do not yield a unique answer as to how the evolutionary dynamics should unfold. Motivated by this problem, we review the developments that led to the present state of affairs, highlight the accompanying pitfalls, and propose new universal scaling parameters for the dilemma strength. We prove universality by showing that the conditions for an ESS and the expressions for the internal equilibriums in an infinite, well-mixed population subjected to any of the five reciprocity mechanisms depend only on the new scaling parameters. A similar result is shown to hold for the fixation probability of the different strategies in a finite, well-mixed population. Furthermore, by means of numerical simulations, the same scaling parameters are shown to be effective even if the evolution of cooperation is considered on the spatial networks (with the exception of highly heterogeneous setups). We close the discussion by suggesting promising directions for future research including (i) how to handle the dilemma strength in the context of co-evolution and (ii) where to seek opportunities for applying the game theoretical approach with meaningful impact.     

Bonus or flat wage? An experiment into the principal-agent problem

We conduct a simple principal-agent experiment in order to find the effects of information asymmetry on compensation. Our aim is the analysis of the appropriate compensation and its impact on employee’s effort. Furthermore we want to compare the offered compensation and the supplied effort in the version without communication and we want to know whether the experimental observations are consistent with the theoretical considerations.The experimenters found out that compensations observed during the experiment were different from those suggested by the theory and although they were theoretically not enough to induce high effort, we could observe high performance supplied by the agents.     

Evolution of cooperation among mobile agents

We study the effects of mobility on the evolution of cooperation among mobile players, which imitate collective motion of biological flocks and interact with neighbors within a prescribed radius R. Adopting the the prisoner’s dilemma game and the snowdrift game as metaphors, we find that cooperation can be maintained and even enhanced for low velocities and small payoff parameters, when compared with the case that all agents do not move. But such enhancement of cooperation is largely determined by the value of R, and for modest values of R, there is an optimal value of velocity to induce the maximum cooperation level. Besides, we find that intermediate values of R or initial population densities are most favorable for cooperation, when the velocity is fixed. Depending on the payoff parameters, the system can reach an absorbing state of cooperation when the snowdrift game is played. Our findings may help understanding the relations between individual mobility and cooperative behavior in social systems.     

Integrating neighborhoods in the evaluation of fitness promotes cooperation in the spatial prisoner’s dilemma game

A fundamental question of human society is the evolution of cooperation. Many previous studies explored this question via setting spatial background, where players obtain their payoffs by playing game with their nearest neighbors. Another undoubted fact is that the environment plays an important role in the individual development. Inspired by these phenomena, we reconsider the definition of individual fitness which integrates the environment, denoted by the average payoff of all individual neighbors, with the traditional individual payoffs by introducing a selection parameter u. Tuning u equal to zero returns the traditional version, while increasing u bears the influence of environment. We find that considering the environment, i.e., integrating neighborhoods in the evaluation of fitness, promotes cooperation. If we enhance the value of u, the invasion of defection could be resisted better. We also provide quantitative explanations and complete phase diagrams presenting the influence of the environment on the evolution of cooperation. Finally, the universality of this mechanism is testified for different neighborhood sizes, different topology structures and different game models. Our work may shed light on the emergence and persistence of cooperation in our life.     

Evolution of cooperation among mobile agents with heterogenous view radii

In this paper, we study cooperative behavior among mobile agents; the agents have heterogenous view radii and they play the prisoner’s dilemma game with those being within their vision fields. It is found that the cooperation level is remarkably promoted when the heterogeneity of view radii is considered, and the degree distribution of the system is investigated to explain this interesting phenomenon. Moreover, we report that the cooperative behavior is best favored by low density, moderate view radius, and small moving speed. Our findings may be helpful in understanding cooperative behavior in natural and social systems consisting of mobile agents.     

Dynamics of a lattice gas model

Lotka–Volterra equations (LVEs) for mutualisms predict that when mutualistic effects between species are strong, population sizes of the species increase infinitely, which is the so-called divergence problem. Although many models have been established to avoid the problem, most of them are rather complicated. This paper considers a mutualism model of two species, which is derived from reactions on lattice and has a form similar to that of LVEs. Population sizes in the model will not increase infinitely since there is interspecific competition for sites on the lattice. Global dynamics of the model demonstrate essential features of mutualisms and basic mechanisms by which the mutualisms can lead to persistence/extinction of mutualists. Our analysis not only confirms typical dynamics obtained by numerical simulations in a previous work, but also exhibits a new one. Saddle-node bifurcation, transcritical bifurcation and pitchfork bifurcation in the system are demonstrated, while a relationship between saddle-node bifurcation and pitchfork bifurcation in the model is displayed. Numerical simulations validate and extend our conclusions.     

Permanence of a discrete nonlinear N-species cooperation system with time delays and feedback controls

A discrete nonlinear N-species cooperation system with time delays and feedback controls is considered in this paper. Sufficient conditions which ensure the permanence of the system are obtained. It is shown that these conditions are weaker than those of Chen [F.D. Chen, Permanence of a discrete N-species cooperation system with time delays and feedback controls, Appl. Math. Comput. 186(2007) 23-29], that is, our investigation shows that the additional condition in Chen’s paper is not necessary.     

A system-theoretic model for cooperation, interaction and allocation

A system-theoretic approach to cooperation, interaction and allocation is presented that simplifies, unifies and extends the results on classical cooperative games and their generalizations. In particular, a general Weber theory of linear values is obtained and a new theory for local cooperation and general interaction indices is established. The model is dynamic and based on the notion of states of cooperation that change under actions of agents. Careful distinction between “local” states of cooperation and general “system” states leads to a notion of entropy for arbitrary non-negative and efficient allocations and thus to a new information-theoretic criterion for fairness of allocation mechanisms. Shapley allocations, for instance, are exhibited as arising from random walks with maximal entropy. For a large class of cooperation systems, a characterization of game symmetries in terms of λ-values is given. A concept for cores and Weber sets is proposed and it is shown that a Weber set of a game with selection structure always contains the core.     

Supply chain scheduling: Just-in-time environment

We study the benefits of coordinated decision making in a supply chain consisting of a manufacturer, a distributor, and several retailers. The distributor bundles finished goods produced by the manufacturer and delivers them to the retailers to meet their demands. The distributor is responsible for managing finished goods inventory. An optimal production schedule of the manufacturer, if imposed on the distributor, may result in an increased inventory holding cost for the distributor. On the other hand, an optimal distribution schedule of the distributor, if imposed on the manufacturer, may result in an increased production cost for the manufacturer. In this paper we develop mathematical models for individual optimization goals of the two partners and compare the results of these models with the results obtained for a joint optimization model at the system level. We investigate the computational complexities of these scheduling problems. The experimental results indicate that substantial cost savings can be achieved at the system level by joint optimization. We also study conflict and cooperation issues in the supply chain. The cost of conflict of a supply chain partner is a measure of the amount by which the unconstrained optimal cost increases when a decision is to be made under the scheduling constraint imposed by the other partner. We quantify these conflicts and show that the cost of conflicts are significant. We also show that a cooperative decision will generate a positive surplus in the system which can be shared by the two partners to make cooperation and coordination strategy more attractive.