Conservative-Bayesian Mechanism Design
نویسندگان
چکیده
Classical Bayesian mechanism design is “centralized”, that is, the designer is assumed to know thedistribution D from which the players’ type profile has been drawn. We instead investigate a very “de-centralized” Bayesian model, where the designer has no knowledge at all, and each player only has someprobabilistic information about D.For this decentralized model and many contexts of interest, where the goal is to maximize revenue,we show that, for arbitrary type distributions D (in particular, correlated ones), it is possible to designmechanisms matching to a significant extent the performance of the optimal centralized mechanisms.Our results are “existential” for a broad class of contexts (including combinatorial auctions) and “con-structive” for auctions of a single good. ∗This work has been partially funded by the Office of Naval Research under award number N00014091059. (Any opinions,findings, and conclusions or recommendations expressed in this email are those of the author (s) and do not necessarily reflectthe views of the Office of Naval Research.)
منابع مشابه
Conservative-Bayesian Mechanisms
We put forward a new class of mechanisms. In this extended abstract, we exemplify our approach only for single-good auctions in what we call a conservative-Bayesian setting. (Essentially, no commonknowledge about the underlying distribution of the players’ valuations is required.) We prove that our mechanism is optimal in this challenging and realistic setting.
متن کاملConservative Rationalizability and The Second-Knowledge Mechanism
In mechanism design, the traditional way of modeling the players’ incomplete information about their opponents is “assuming a Bayesian.” This assumption, however, is very strong and does not hold in many real applications. Accordingly, we put forward (1) a set-theoretic way to model the knowledge that a player might have about his opponents, and (2) a new class of mechanisms capable of leveragi...
متن کاملAn Efficient Bayesian Optimal Design for Logistic Model
Consider a Bayesian optimal design with many support points which poses the problem of collecting data with a few number of observations at each design point. Under such a scenario the asymptotic property of using Fisher information matrix for approximating the covariance matrix of posterior ML estimators might be doubtful. We suggest to use Bhattcharyya matrix in deriving the information matri...
متن کاملBayesian Optimum Design Criterion for Multi Models Discrimination
The problem of obtaining the optimum design, which is able to discriminate between several rival models has been considered in this paper. We give an optimality-criterion, using a Bayesian approach. This is an extension of the Bayesian KL-optimality to more than two models. A modification is made to deal with nested models. The proposed Bayesian optimality criterion is a weighted average, where...
متن کاملBayesian Mechanism Design with Efficiency, Privacy, and Approximate Truthfulness
Recently, there has been a number of papers relating mechanism design and privacy (e.g., see [MT07, Xia11, CCK11, NST12, NOS12, HK12]). All of these papers consider a worst-case setting where there is no probabilistic information about the players’ types. In this paper, we investigate mechanism design and privacy in the Bayesian setting, where the players’ types are drawn from some common distr...
متن کامل