Approximately Revenue-Maximizing Auctions for Deliberative Agents

In many real-world auctions, a bidder does not know her exact value for an item, but can perform costly deliberation to reduce uncertainty. Relatively little is known about such deliberative environments, which are fundamentally different from classical auction environments. this paper, we propose new approach that allows us leverage revenue-maximization results in particular, use Myerson (1981) construct the first non-trivial (i.e., dependent on costs) upper bound revenue auctions. This apply existing environment environment. addition, show environments only optimal dominant-strategy mechanisms take form of sequential posted-price