The University of Southampton
University of Southampton Institutional Repository

Fair allocation of resources with uncertain availability

Fair allocation of resources with uncertain availability
Fair allocation of resources with uncertain availability
Multi-agent resource allocation is an important and well-studied problem within AI and economics. It is generally assumed that the quantity of each resource is known a priori. However, in many real-world problems, such as the production of renewable energy which is typically weather dependent, the exact amount of each resource may not be known at the time of decision making. In this paper we investigate fair division of a homogeneous divisible resource where the available amount is given by a probability distribution. Specifically, we study the notion of ex-ante envy-freeness, where, in expectation, agents weakly prefer their allocation over every other agent's allocation. We analyse the trade-off between fairness and social welfare. We show that allocations satisfying ex-ante envy-freeness can result in higher social welfare compared to those satisfying ex-post envy-freeness. Nevertheless, the price of envy-freeness is at least $\Omega(n)$, where $n$ is the number of agents, and this is tight under concave valuation functions. Principally, we show that the problem of optimising ex-ante social welfare subject to ex-ante envy-freeness is NP-hard in the strong sense. Finally, we devise an integer program to calculate the optimal ex-ante envy-free allocation for linear satiable valuation functions.
Fair allocation, Social choice theory
Buermann, Jan
d12aad54-d71f-4eba-9510-daf0ee2c7fc3
Gerding, Enrico
d9e92ee5-1a8c-4467-a689-8363e7743362
Rastegari, Baharak
6ba9e93c-53ba-4090-8f77-c1cb1568d7d1
Buermann, Jan
d12aad54-d71f-4eba-9510-daf0ee2c7fc3
Gerding, Enrico
d9e92ee5-1a8c-4467-a689-8363e7743362
Rastegari, Baharak
6ba9e93c-53ba-4090-8f77-c1cb1568d7d1

Buermann, Jan, Gerding, Enrico and Rastegari, Baharak (2020) Fair allocation of resources with uncertain availability. Nineteenth International Conference on Autonomous Agents and Multi-Agent Systems, New Zealand. 09 - 13 May 2020. 9 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

Multi-agent resource allocation is an important and well-studied problem within AI and economics. It is generally assumed that the quantity of each resource is known a priori. However, in many real-world problems, such as the production of renewable energy which is typically weather dependent, the exact amount of each resource may not be known at the time of decision making. In this paper we investigate fair division of a homogeneous divisible resource where the available amount is given by a probability distribution. Specifically, we study the notion of ex-ante envy-freeness, where, in expectation, agents weakly prefer their allocation over every other agent's allocation. We analyse the trade-off between fairness and social welfare. We show that allocations satisfying ex-ante envy-freeness can result in higher social welfare compared to those satisfying ex-post envy-freeness. Nevertheless, the price of envy-freeness is at least $\Omega(n)$, where $n$ is the number of agents, and this is tight under concave valuation functions. Principally, we show that the problem of optimising ex-ante social welfare subject to ex-ante envy-freeness is NP-hard in the strong sense. Finally, we devise an integer program to calculate the optimal ex-ante envy-free allocation for linear satiable valuation functions.

Text
Fair_Allocation_of_Resources_with_Uncertain_Availability - Accepted Manuscript
Available under License Other.
Download (745kB)

More information

Accepted/In Press date: 15 January 2020
Published date: May 2020
Venue - Dates: Nineteenth International Conference on Autonomous Agents and Multi-Agent Systems, New Zealand, 2020-05-09 - 2020-05-13
Keywords: Fair allocation, Social choice theory

Identifiers

Local EPrints ID: 438331
URI: http://eprints.soton.ac.uk/id/eprint/438331
PURE UUID: f3bcbc4a-5867-4d8e-9f90-8bf680f9825c
ORCID for Jan Buermann: ORCID iD orcid.org/0000-0002-4981-6137
ORCID for Enrico Gerding: ORCID iD orcid.org/0000-0001-7200-552X
ORCID for Baharak Rastegari: ORCID iD orcid.org/0000-0002-0985-573X

Catalogue record

Date deposited: 06 Mar 2020 17:30
Last modified: 13 May 2020 04:01

Export record

Contributors

Author: Jan Buermann ORCID iD
Author: Enrico Gerding ORCID iD
Author: Baharak Rastegari ORCID iD

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×