Single and Multi-Dimensional Optimal Auctions - A Network Approach

This paper highlights connections between the discrete and continuous approaches to optimal auction design with single and multi-dimensional types. We provide an interpretaion of an optimal auction design problem in terms of a linear program that is an instance of a parametric shortest path problem on a lattice. We also solve some cases explicitly in the discrete framework.Auctions, Networks, Linear Programming

Dominant Strategy Mechanisms with Multidimensional Types

This paper provides a characterization of dominant strategy mechanisms with quasi-linear utilities and multi-dimensional types for a variety of preference domains. These characterizations are in terms of a monotonicity property on the underlying allocation rule

Dominant Strategy Mechanisms with Multidimensional Types

This paper provides a characterization of dominant strategy mechanisms with quasi-linear utilities and multi-dimensional types for a variety of preference domains. These characterizations are in terms of a monotonicity property on the underlying allocation rule.Dominant Strategy, Farkas Lemma, Combinatorial Auctions.

Calibrated Learning and Correlated Equilibrium

Suppose two players repeatedly meet each other to play a game where: 1. each uses a learning rule with the property that it is a calibrated forecast of the other\u27s plays, and 2. each plays a myopic best response to this forecast distribution. Then, the limit points of the sequence of plays are correlated equilibria. In fact, for each correlated equilibrium there is some calibrated learning rule that the players can use which results in their playing this correlated equilibrium in the limit. Thus, the statistical concept of a calibration is strongly related to the game theoretic concept of correlated equilibrium

Strategy-proof Location on a Network

We consider rules that choose a location on a graph (e.g. a network of roads) based on the report of agents' symmetric, single-peaked preferences over points on that graph. We show that while a strategy-poof, onto rule is not necessarily dictatorial, the existence of a cycle on the graph grants one agent a certain amount of decisive power. This result surprisingly characterizes the class of strategy-proof, onto rules both in terms of a certain subclass of such rules for trees and in terms of a parameterized set of generalized median voter schemes.

Calibration, Expected Utility and Local Optimality

We propose a framework for reconciling frequentist and subjectivist views of probability. In an environment with repeated trails we show that beliefs about the possible states of nature can be represented by probabilities. Second, these probabilities will correspond to long run frequencies. In particular they will be naively calibrated. Third, the actions chosen in each trial will be the ones that maximize expected utility on that trial. The expectation is with respect to the probabilities used to represent beliefs.