Fairness in Combinatorial Auctions

TL;DR

This paper explores fairness in combinatorial auctions by defining basic and extended fairness, proposing algorithms to ensure fairness using Generalized Vickrey Auctions, and analyzing these concepts under dominant strategy solutions.

Contribution

It introduces a novel fairness framework in combinatorial auctions and provides algorithms to implement fairness within the GVA setting.

Findings

Algorithms ensure fairness in CAS using GVA

Fairness concepts are analyzed under dominant strategies

Optimality achieved with Sandholm's algorithm

Abstract

The market economy deals with many interacting agents such as buyers and sellers who are autonomous intelligent agents pursuing their own interests. One such multi-agent system (MAS) that plays an important role in auctions is the combinatorial auctioning system (CAS). We use this framework to define our concept of fairness in terms of what we call as "basic fairness" and "extended fairness". The assumptions of quasilinear preferences and dominant strategies are taken into consideration while explaining fairness. We give an algorithm to ensure fairness in a CAS using a Generalized Vickrey Auction (GVA). We use an algorithm of Sandholm to achieve optimality. Basic and extended fairness are then analyzed according to the dominant strategy solution concept.