The Effects of Developer Dynamics on Fitness in an Evolutionary Ecosystem Model of the App Store
通过扩展的AppEco模型模拟2008-2014年iOS应用商店，研究开发者策略（创新者、模仿者等）对应用下载适应度的影响，发现模仿者策略虽成功但需与优化者共存才能达到最佳适应度。
Natural ecosystems exhibit complex dynamics of interacting species. Man-made ecosystems exhibit similar dynamics and, in the case of mobile app stores, can be said to perform optimization as developers seek to maximize app downloads. This work aims to understand stability and instability within app store dynamics and how it affects fitness. The investigation is carried out with AppEco, a model of the iOS App Store, which was extended for this paper and updated to model the store from 2008 to 2014. AppEco models apps containing features, developers who build the apps, users who download apps according to their preferences, and an app store that presents apps to the users. It also models developers who use commonly observed strategies to build their apps: innovator, milker, optimizer, copycat, and flexible (the ability to choose any strategy). Results show that despite the success of the copycat strategy, there is a clear stable state for low proportion of copycats in developer populations, mirroring results in theoretical biology for producer-scrounger systems. The results also show that the best fitness is achieved when the evolutionary optimizer (as producer) and copycat (as scrounger) strategies coexist together in stable proportions.