The sequential online chore division problem - definition and application

Harel Yedidsion, Shani Alkoby, Peter Stone

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper defines a novel formulation of chore division, called Sequential Online Chore Division (SOCD), in which participants arrive and depart online, while the chore is being performed. In SOCD, there exists some uncertainty both regarding the total number of participants and their arrival/departure times. Moreover, only one agent can perform the chore at any given moment, and switching the performer incurs a cost. This novel variant of chore division can model real world problems such as the autonomous vehicle convoy formation problem, which has significant social implications. Autonomous vehicles are said to form a convoy when vehicles headed in the same direction follow each other in close proximity. This behavior has been proven to save energy, due to the reduction in aerodynamic drag. Empirical evaluations estimate that a follower can save over 10% of its fuel consumption [1]. However, since the leader sees little or no such gains, choosing the leader of such a convoy raises issues of fairness, and efficiency. Solving these issues is challenging since vehicles can dynamically join and leave the convoy. To address this problem, we propose three mechanisms for fair chore division. The first mechanism is centralized and uses side payments while the other two are distributed and seek to balance the participants' loads. We show that the payment-transfer mechanism, which requires a centralized server, results in optimal fairness and efficiency. For the cases where a central server is not available, we show that the repeated-game mechanism produces allocations which are efficiently-optimal and fair in expectation. For the single-game case, we first prove that optimal fairness is impossible to guarantee. We then show that our proposed single-game mechanism, which offers minimal efficiency loss, achieves ex-ante proportionality.

Original languageEnglish
Title of host publicationProceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020
EditorsBo An, Amal El Fallah Seghrouchni, Gita Sukthankar
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages2059-2061
Number of pages3
ISBN (Electronic)9781450375184
StatePublished - 2020
Externally publishedYes
Event19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020 - Virtual, Auckland, New Zealand
Duration: 19 May 2020 → …

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume2020-May
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

Conference19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020
Country/TerritoryNew Zealand
CityVirtual, Auckland
Period19/05/20 → …

Bibliographical note

Publisher Copyright:
© 2020 International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). All rights reserved.

Funding

This work has taken place in the Learning Agents Research Group (LARG) at UT Austin. LARG research is supported in part by NSF (CPS-1739964, IIS-1724157, NRI-1925082), ONR (N00014-18-2243), FLI (RFP2-000), ARL, DARPA, Lockheed Martin, GM, and Bosch. Peter Stone serves as the Executive Director of Sony AI America and receives financial compensation for this work. The terms of this arrangement have been reviewed and approved by the University of Texas at Austin in accordance with its policy on objectivity in research. We acknowledge the contribution of Mr. Vinay Shukla to a preliminary version of this work.

FundersFunder number
FLIRFP2-000
National Science FoundationIIS-1724157, NRI-1925082, CPS-1739964
Office of Naval ResearchN00014-18-2243
Defense Advanced Research Projects Agency
Association of Research Libraries
Robert Bosch

    Keywords

    • Autonomous Vehicles
    • Chore Division
    • Convoy Formation
    • Mechanism Design
    • Multi Agent Coordination
    • Platooning

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