Welfare Maximization and Truthfulness in Mechanism Design with Ordinal Preferences
Deeparnab Chakrabarty, Chaitanya Swamy

TL;DR
This paper introduces new metrics and truthfulness concepts for ordinal mechanism design, enabling the creation of mechanisms that maximize social welfare and are resistant to classical impossibility results.
Contribution
It proposes rank approximation and lex-truthfulness, facilitating the design of effective, truthful mechanisms in ordinal settings where utilities are not explicitly known.
Findings
Developed rank approximation as a welfare measurement tool.
Introduced lex-truthfulness as a stronger, flexible truthfulness notion.
Designed mechanisms achieving good rank-approximation in various market settings.
Abstract
We study mechanism design problems in the {\em ordinal setting} wherein the preferences of agents are described by orderings over outcomes, as opposed to specific numerical values associated with them. This setting is relevant when agents can compare outcomes, but aren't able to evaluate precise utilities for them. Such a situation arises in diverse contexts including voting and matching markets. Our paper addresses two issues that arise in ordinal mechanism design. To design social welfare maximizing mechanisms, one needs to be able to quantitatively measure the welfare of an outcome which is not clear in the ordinal setting. Second, since the impossibility results of Gibbard and Satterthwaite~\cite{Gibbard73,Satterthwaite75} force one to move to randomized mechanisms, one needs a more nuanced notion of truthfulness. We propose {\em rank approximation} as a metric for measuring the…
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Taxonomy
TopicsGame Theory and Voting Systems · Auction Theory and Applications · Experimental Behavioral Economics Studies
