RTRC:A Reputation-Based Incentive Game Model for Trustworthy Crowdsourcing Service

The ubiquity of mobile devices have promoted the prosperity of mobile crowd systems, which recruit crowds to contribute their resources for performing tasks. Yet, due to the various resource consumption, the crowds may be reluctant to join and contribute information. Thus, the low participation level of crowds will be a hurdle that prevents the adoption of crowdsourcing. A critical challenge for these systems is how to design a proper mechanism such that the crowds spontaneously act as suppliers to contribute accurate information. Most of existing mechanisms ignore either the honesty of crowds or requesters respectively. In this paper, considering the honesty of both, we propose a game-based incentive mechanism, namely RTRC, to stimulate the crowds to contribute accurate information and to motivate the requesters to return accurate feedbacks. In addition, an evolutionary game is designed to model the dynamic of user-strategy selection. Specially, the replicator dynamic is applied to model the adaptation of strategy interactions taking into account the dynamic nature in time dependence and we also derive the evolutionarily stable strategies(ESSs) for users. Finally, empirical results over the simulations show that all the requesters and suppliers will select honest strategy to maximize their profit.

Habitat destruction may lead to highly female-biased sex ratios

Local mate competition(LMC) was firstly used to explain extra-ordinary female-biased sex ratios. However, some observations have found that the sex ratios of some species are more female-biased than the predictions of LMC and its extensions; there is not yet a theory that accounts for the mechanisms of more female-biased sex ratio. Here, we assume that LMC occurs at a destructed habitat that reduces the resource for production, and present a new extension for the LMC model. Consequently, our model shows that the evolutionarily stable strategy(ESS) for sex ratio depends on two parameters: the number of foundresses and the degree of habitat destruction. Moreover, the sex ratio decreases as the degree of habitat destruction increases, i.e., the proportion of female increases. These results generally agree with experimental data, and may provide a new basis for the evolution of female-biased sex ratios in local mate competition and a new theory support for conservation of some species.

A tripartite evolutionary game analysis of providing subsidies for pick-up/drop-off strategy in carpooling problem

Although the pick-up/drop-off(PUDO)strategy in carpooling offers the convenience of short-distance walking for passengers during boarding and disembarking,there is a noticeable hesitancy among commuters to adopt this travel method,despite its numerous benefits.Here,this paper establishes a tripartite evolutionary game theory(EGT)model to verify the evolutionary stability of choosing the PUDO strategy of drivers and passengers and offering subsidies strategy of carpooling platforms in carpooling system.The model presented in this paper serves as a valuable tool for assessing the dissemination and implementation of PUDO strategy and offering subsidies strategy in carpooling applications.Subsequently,an empirical analysis is conducted to examine and compare the sensitivity of the parameters across various scenarios.The findings suggest that:firstly,providing subsidies to passengers and drivers,along with deductions for drivers through carpooling platforms,is an effective way to promote wider adoption of the PUDO strategy.Then,the decision-making process is divided into three stages:initial stage,middle stage,and mature stage.PUDO strategy progresses from initial rejection to widespread acceptance among drivers in the middle stage and,in the mature stage,both passengers and drivers tend to adopt it under carpooling platform subsidies;the factors influencing the costs of waiting and walking times,as well as the subsidies granted to passengers,are essential determinants that require careful consideration by passengers,drivers,and carpooling platforms when choosing the PUDO strategy.Our work provides valuable insight into the PUDO strategy’s applicability and the declared results provide implications for traffic managers and carpooling platforms to offer a suitable incentive.