Strategic decisions are increasingly delegated to algorithms. We extend the results of Waltman and Kaymak [2008] and Calvano et al. [2020b] to the context of dynamic optimization with imperfect monitoring by analyzing a setting where a limited number of agents use simple and independent...

A burgeoning literature shows that self-learning algorithms may, under some conditions, reach seemingly-collusive outcomes: after repeated interaction, competing algorithms earn supra-competitive profits, at the expense of efficiency and consumer welfare. However, these simulations results,...