The future of algorithmic competition: a network-based perspective

数字平台日益主导数字经济和实体经济。它们的崛起及其对市场的影响正受到政界人士和监管机构的密切关注，他们担心这些平台上使用的算法会如何改变在线竞争的性质。竞争法、经济学和监管机构都强调了算法促进串通的潜力。尽管这个话题与社会相关，但缺乏关于如何防止算法以牺牲消费者为代价阻碍竞争的数学研究。该项目在网络科学、经济学和机器学习的交叉领域开创了广泛的跨学科研究方法。我们计划使用网络科学和图论的工具对算法在市场中的行为进行建模，以确定导致与非串通算法进行激烈竞争的条件。我们希望更好地理解并最终解决在线算法问题，促进数字经济中算法的测试程序和标准。

Digital platforms increasingly dominate the digital and physical economy. Their rise and subsequent impact on markets is being scrutinized by politicians and regulators, concerned about the use of algorithms on these platforms, on how this might change the nature of competition online. The potential of algorithms to facilitate collusion has been emphasized in competition law, in economics, and by regulators. Despite the relevance of the topic to society, there is a lack of mathematical research on how to prevent algorithms from hindering competition at the expense of consumers.This project initiates a broad interdisciplinary research approach at the intersection of network science, economics, and machine learning. We plan to model the behavior of algorithms in a market using tools from network science and graph theory, in order to determine the conditions that lead to strong competition with non-collusive algorithms. We hope to better understand and ultimately address algorithmic concerns online, to foster testing procedures and standards for algorithms in the digital economy.