We consider a robust version of the classic problem of optimal monopoly pricing with incomplete information. The robust version of the problem is distinct in two aspects: (i) the seller minimizes regret rather than maximizes revenue, and (ii) the seller only knows that the true distribution of the valuations is in a neighborhood of a given model distribution. We characterize the robust pricing policy as the solution to a minimax problem for small and large neighborhoods. In contrast to the classic monopoly policy, which is a single deterministic price, the robust policy is always a random pricing policy, or equivalently, a multi-item menu policy. The responsiveness of the robust policy to an increase in risk is determined by the curvature of the static proﬁt function.
Bergemann, Dirk and Schlag, Karl, "Robust Monopoly Pricing: The Case of Regret" (2005). Cowles Foundation Discussion Papers. 1811.