Dynamic pricing and reinforcement learning

We consider the problem of optimizing sales revenues based on a parametric model in which the parameters are unknown. The manager has to set the price at a level in order to maximize current revenues and at the same time learn about the parameter values to increase the future revenues. Both demand and price are assumed to be continuous variables. We study several different strategies for learning and show that a one-step look-ahead rule produces good short term performance.