Pricing Without Priors
卖家只知道买家估值的可能范围，没有分布信息，通过随机化定价来最小化遗憾，低估值买家被排除在市场之外。
We consider the problem of pricing a single object when the seller has only minimal information about the true valuation of the buyer. Speci cally, the seller only knows the support of the possible valuations and has no further distributional information. The seller is solving this choice problem under uncertainty by minimizing her regret. The pricing policy hedges against uncertainty by randomizing over a range of prices. The support of the pricing policy is bounded away from zero. Buyers with low valuations cannot generate substantial regret and are priced out of the market. We generalize the pricing policy without priors to encompass many buyers and many qualities.