Classic artificial intelligence (Q-learning) algorithms have been capable of consistently learning supra-competitive pricing strategies in infinitely repeated Nash-Bertrand pricing games without human communication. Such algorithms have been able to converge due to the temporal correlation of...

We propose a distributed randomized policy iteration algorithm for infinite horizon dynamic programming problems for which the control at each stage is m-dimensional. The traditional policy iteration algorithm involves performing a minimization over an m-dimensional constraint set and has a...

Airfares vary across the booking horizon according to intertemporal price discrimination and adjustment of fares in response to stochastic demand shocks. Previous works studying these economic forces abstract away from the ramifications of pricing an itinerary has on revenue and consumer welfare...