Modeling And Analysing Of Game Dynamics In Crowdsourcing System

In recent years,with the rapid development of the Internet,a new business model in-novation——Crowdsourcing came into being.Crowdsourcing show the huge commercial charm favored large enterprises.However,the rational and selfish workers in crowd-sourcing systems aim to strategically maximize their own benefit by exhibiting malicious behaviors,thus decreasing the efficiency of systems.Therefore,a crucial question in the MCS is as follows:How to design an effective mechanism to encourage cooperation and guarantee high-quality solutions in social welfare among selfish workers?In the previous papers,the main research,is based on the price incentive mechanism and the reputation incentive mechanism.On the one hand,due to the heterogeneity in tasks and requesters,the existing pricing scheme often provides competitive advantages to the requesters with high budgets.On the other hand,the reputation mechanism often needs necessary traffic monitoring mechanisms and involves a more complicated reputa-tion update.Most importantly,these two incentive mechanisms do not fundamentally solve the " free-riding" behavior in the crowdsourcing system.This thesis will use the game theory to study crowdsourcing users behavior.Fundamentally promoting workers to work hard to submit high-quality solutions.This paper will conduct a detailed research on the macro-crowdsourcing system,through the introduction of the game of ideas to design incentives,Promoting mutual cooperation among task workers and optimizing the performance of the crowdsourcing systems?This paper establishes a game model between task workers which is similar the public goods game?On the one hand,we analysis the game model;on the other hand,we adopt the repeated game,while the introduction of zero-determinant strategy makes the worker who takes the zero-determinant strategy can unilaterally control the social welfare.