30 research outputs found
Online Fair Division: A Survey
We survey a burgeoning and promising new research area that considers the
online nature of many practical fair division problems. We identify wide
variety of such online fair division problems, as well as discuss new
mechanisms and normative properties that apply to this online setting. The
online nature of such fair division problems provides both opportunities and
challenges such as the possibility to develop new online mechanisms as well as
the difficulty of dealing with an uncertain future.Comment: Accepted by the 34th AAAI Conference on Artificial Intelligence (AAAI
2020
Allocation in Practice
How do we allocate scarcere sources? How do we fairly allocate costs? These
are two pressing challenges facing society today. I discuss two recent projects
at NICTA concerning resource and cost allocation. In the first, we have been
working with FoodBank Local, a social startup working in collaboration with
food bank charities around the world to optimise the logistics of collecting
and distributing donated food. Before we can distribute this food, we must
decide how to allocate it to different charities and food kitchens. This gives
rise to a fair division problem with several new dimensions, rarely considered
in the literature. In the second, we have been looking at cost allocation
within the distribution network of a large multinational company. This also has
several new dimensions rarely considered in the literature.Comment: To appear in Proc. of 37th edition of the German Conference on
Artificial Intelligence (KI 2014), Springer LNC
Nash Welfare and Facility Location
We consider the problem of locating a facility to serve a set of agents
located along a line. The Nash welfare objective function, defined as the
product of the agents' utilities, is known to provide a compromise between
fairness and efficiency in resource allocation problems. We apply this welfare
notion to the facility location problem, converting individual costs to
utilities and analyzing the facility placement that maximizes the Nash welfare.
We give a polynomial-time approximation algorithm to compute this facility
location, and prove results suggesting that it achieves a good balance of
fairness and efficiency. Finally, we take a mechanism design perspective and
propose a strategy-proof mechanism with a bounded approximation ratio for Nash
welfare