Adaptive interaction driven by the learning effect in the spatial prisoner's dilemma

We propose a computing model in which individuals can automatically adjust their interaction intensity with their mentor according to the learning effect.This model is designed to investigate the cooperative dynamics of the spatial prisoner's dilemma.More specifically,when the cumulative payoff of a learner is more than his reference earning,he will strengthen his interaction with his mentor;otherwise,he will reduce it.The experimental results indicate that this mechanism can improve the emergence of cooperation in a networked population and that the driving coefficient of interaction intensity plays an important role in promoting cooperation.Interestingly,under a certain social dilemma condition,there exists a minimal driving coefficient that leads to optimal cooperation.This occurs due to a positive feedback effect between the individual's satisfaction frequency and the number of effective neighbors.Moreover,we find that the experimental results are in accord with theoretical predictions obtained from an extension of the classical pair-approximation method.Our conclusions obtained by considering relationships with mentors can provide a new perspective for future investigations into the dynamics of evolutionary games within structured populations.

Inference of interactions between players based on asynchronously updated evolutionary game data

The interactions between players of the prisoner's dilemma game are inferred using observed game data.All participants play the game with their counterparts and gain corresponding rewards during each round of the game.The strategies of each player are updated asynchronously during the game.Two inference methods of the interactions between players are derived with naive mean-field(n MF)approximation and maximum log-likelihood estimation(MLE),respectively.Two methods are tested numerically also for fully connected asymmetric Sherrington-Kirkpatrick models,varying the data length,asymmetric degree,payoff,and system noise(coupling strength).We find that the mean square error of reconstruction for the MLE method is inversely proportional to the data length and typically half(benefit from the extra information of update times)of that by n MF.Both methods are robust to the asymmetric degree but work better for large payoffs.Compared with MLE,n MF is more sensitive to the strength of couplings and prefers weak couplings.

哥梯尔的“协议道德”理论评析

哥梯尔在《协议道德》一书中,试图完全从个人利益出发推导出道德的原则。具体地讲,哥梯尔极力想证明:第一,有理性的个人在相互交往中,遇到类似"囚徒悖论"情景中的次佳化问题时,愿意接受公正的、不偏不倚的限制性条款(即道德的原则),用以限制个人无止境地追求个人利益,从而避免次佳化问题,并实现共同的利益;第二,一旦达成限制性条款或协议,各方遵守条款或协议是符合理性的,即符合各方的个人利益的。以上两点在"重复性的囚徒悖论"情景中得到了很好的证明,但哥梯尔的"协议道德"理论仍然有其局限性。

Natural selection bet ween two games with environmentai feedback

Evolutionary game theory has extensively investigated situations in which several gamesare competing against each other at the same time,but the model only assumes sym-metric interactions in homogeneous environments.Now,the population is consideredin heterogeneous environments,individuals in the population occupy a different qualityof patches,and individual fitness depends not only on the interaction between individ-uals,but also on the quality of the environment.Here,by establishing a mathemati-cal framework,we analyze the natural selection between two strategies and two gamesin heterogeneous environments.Furthermore,we analyze the natural selection of Pris-oner's Dilemma and Hawk-Dove games theoretically to demonstrate the dynamics ofcooperators and defectors in their choice of environment and their respective games.Asexpected,the distribution of games and strategies changes with time.Based on differentinitial population compositions,we also discuss the invasion problem of games from dif-ferent perspectives.To one's surprise,we can find that good quality patches attract allindividuals;the long-term dynamics in invariant rich environments is the same as thedynamics of symmetric interactions in homogeneous environments.

Drop-shipping or batch ordering: Contract choice in the presence of information sharing and quality decision

This study investgates the manufacturer's contract choice(drop shipping or batch ordering)and retailer's information sharing strategy in the presence of product quality decisions.The equilibr ium outcomes give strategic choices for both the manufacturer and retailer.Specifically,the retailer prefers to share demand information when the quality investment efficiency is high under batch ordering contract,while he always chooses to share information under drop-shipping contract.Given no information sharing,the manufacturer chooses the batch ordering contract if the revenue-sharing rate is high.Given information sha ring,the manufacturer prefers batch ordering contract when either of the ollowing conditions holds:a)when the revenue-sharing rate is low and quality investment efficiency is low;b)when the revenwe-sharing rate is high and quality in-vestment efficiency is high;otherwise,the manufacturer prefers drop-shipping contract.Additionally,our results indicate that there may exist a"prisoner's dilemma"when the drop-shipping contract is a dominant strategy for the manufacturer and sharing demand information is a dominant strategy for the retailer.