Algorithmic collusion under sequential pricing and stochastic costs

The use of pricing algorithms raises concerns about algorithmic collusion. This paperconsiders a sequential pricing model where marginal cost fluctuates over time. I findthat Q-learning algorithms autonomously collude even under cost uncertainty. Collusionis sustained by strategies that involve reward-punishment schemes. It suggeststhat cost uncertainty is not an obstacle to autonomous algorithmic collusion.