Mechanisms with costly knowledge

Abstract

Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.Cataloged from PDF version of thesis.Includes bibliographical references (pages 18-21).We propose investigating the design and analysis of game theoretic mechanisms when the players have very unstructured initial knowledge about themselves, but can refine their own knowledge at a cost. We consider several set-theoretic models of "costly knowledge". Specifically, we consider auctions of a single good in which a player i's only knowledge about his own valuation, [theta]i, is that it lies in a given interval [a, b]. However, the player can pay a cost, depending on a and b (in several ways), and learn a possibly arbitrary but shorter (in several metrics) sub-interval, which is guaranteed to contain [theta]i. In light of the set-theoretic uncertainty they face, it is natural for the players to act so as to minimize their regret. As a first step, we analyze the performance of the second-price mechanism in regret-minimizing strategies, and show that, in all our models, it always returns an outcome of very high social welfare.by Atalay M. Ileri.S.M