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We consider the problem of designing revenue-maximizing online posted-price mechanisms when the seller has limited supply. A seller has k identical items for sale and is facing n potential buyers (“agents”) that are arriving sequentially. Each agent is interested in buying one item. Each agent’s value for an item is an independent sample from some fixed (but unknown) distribution with support [0,1]. The seller offers a take-it-or-leave-it price to each arriving agent (possibly different for different agents), and aims to maximize his expected revenue.

We focus on mechanisms that do not use any information about the distribution; such mechanisms are called detail-free (or prior-independent). They are desirable because knowing the distribution is unrealistic in many practical scenarios. We study how the revenue of such mechanisms compares to the revenue of the optimal offline mechanism that knows the distribution …