• Skip to main content
  • Skip to primary sidebar
AAAI

AAAI

Association for the Advancement of Artificial Intelligence

    • AAAI

      AAAI

      Association for the Advancement of Artificial Intelligence

  • About AAAIAbout AAAI
    • AAAI Officers and Committees
    • AAAI Staff
    • Bylaws of AAAI
    • AAAI Awards
      • Fellows Program
      • Classic Paper Award
      • Dissertation Award
      • Distinguished Service Award
      • Allen Newell Award
      • Outstanding Paper Award
      • Award for Artificial Intelligence for the Benefit of Humanity
      • Feigenbaum Prize
      • Patrick Henry Winston Outstanding Educator Award
      • Engelmore Award
      • AAAI ISEF Awards
      • Senior Member Status
      • Conference Awards
    • AAAI Resources
    • AAAI Mailing Lists
    • Past AAAI Presidential Addresses
    • Presidential Panel on Long-Term AI Futures
    • Past AAAI Policy Reports
      • A Report to ARPA on Twenty-First Century Intelligent Systems
      • The Role of Intelligent Systems in the National Information Infrastructure
    • AAAI Logos
    • News
  • aaai-icon_ethics-diversity-line-yellowEthics & Diversity
  • Conference talk bubbleConferences & Symposia
    • AAAI Conference
    • AIES AAAI/ACM
    • AIIDE
    • IAAI
    • ICWSM
    • HCOMP
    • Spring Symposia
    • Summer Symposia
    • Fall Symposia
    • Code of Conduct for Conferences and Events
  • PublicationsPublications
    • AAAI Press
    • AI Magazine
    • Conference Proceedings
    • AAAI Publication Policies & Guidelines
    • Request to Reproduce Copyrighted Materials
  • aaai-icon_ai-magazine-line-yellowAI Magazine
    • Issues and Articles
    • Author Guidelines
    • Editorial Focus
  • MembershipMembership
    • Member Login
    • Developing Country List
    • AAAI Chapter Program

  • Career CenterCareer Center
  • aaai-icon_ai-topics-line-yellowAITopics
  • aaai-icon_contact-line-yellowContact

Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 36 / No. 5: AAAI-22 Technical Tracks 5

Maximizing Nash Social Welfare in 2-Value Instances

February 1, 2023

Download PDF

Authors

Hannaneh Akrami

Max Planck Institute for Informatics Graduiertenschule Informatik, Universität des Saarlandes


Bhaskar Ray Chaudhury

University of Illinois, Urbana-Champaign, Department of Computer Science


Martin Hoefer

Goethe University Frankfurt, Institute for Computer Science


Kurt Mehlhorn

Max Planck Institute for Informatics, Universität des Saarlandes


Marco Schmalhofer

Goethe University Frankfurt, Institute for Computer Science


Golnoosh Shahkarami

Max Planck Institute for Informatics Graduiertenschule Informatik, Universität des Saarlandes


Giovanna Varricchio

Goethe University Frankfurt, Institute for Computer Science


Quentin Vermande

École Normale Supérieure, Paris


Ernest van Wijland

École Normale Supérieure, Paris


DOI:

10.1609/aaai.v36i5.20402


Abstract:

We consider the problem of maximizing the Nash social welfare when allocating a set G of indivisible goods to a set N of agents. We study instances, in which all agents have 2-value additive valuations: The value of every agent for every good is either p or q, where p and q are integers and p2. In terms of approximation, we present positive and negative results for general p and q. We show that our algorithm obtains an approximation ratio of at most 1.0345. Moreover, we prove that the problem is APX-hard, with a lower bound of 1.000015 achieved at p/q = 4/5.

Topics: AAAI

Primary Sidebar

HOW TO CITE:

Hannaneh Akrami||Bhaskar Ray Chaudhury||Martin Hoefer||Kurt Mehlhorn||Marco Schmalhofer||Golnoosh Shahkarami||Giovanna Varricchio||Quentin Vermande||Ernest van Wijland Maximizing Nash Social Welfare in 2-Value Instances Proceedings of the AAAI Conference on Artificial Intelligence (2022) 4760-4767.

Hannaneh Akrami||Bhaskar Ray Chaudhury||Martin Hoefer||Kurt Mehlhorn||Marco Schmalhofer||Golnoosh Shahkarami||Giovanna Varricchio||Quentin Vermande||Ernest van Wijland Maximizing Nash Social Welfare in 2-Value Instances AAAI 2022, 4760-4767.

Hannaneh Akrami||Bhaskar Ray Chaudhury||Martin Hoefer||Kurt Mehlhorn||Marco Schmalhofer||Golnoosh Shahkarami||Giovanna Varricchio||Quentin Vermande||Ernest van Wijland (2022). Maximizing Nash Social Welfare in 2-Value Instances. Proceedings of the AAAI Conference on Artificial Intelligence, 4760-4767.

Hannaneh Akrami||Bhaskar Ray Chaudhury||Martin Hoefer||Kurt Mehlhorn||Marco Schmalhofer||Golnoosh Shahkarami||Giovanna Varricchio||Quentin Vermande||Ernest van Wijland. Maximizing Nash Social Welfare in 2-Value Instances. Proceedings of the AAAI Conference on Artificial Intelligence 2022 p.4760-4767.

Hannaneh Akrami||Bhaskar Ray Chaudhury||Martin Hoefer||Kurt Mehlhorn||Marco Schmalhofer||Golnoosh Shahkarami||Giovanna Varricchio||Quentin Vermande||Ernest van Wijland. 2022. Maximizing Nash Social Welfare in 2-Value Instances. "Proceedings of the AAAI Conference on Artificial Intelligence". 4760-4767.

Hannaneh Akrami||Bhaskar Ray Chaudhury||Martin Hoefer||Kurt Mehlhorn||Marco Schmalhofer||Golnoosh Shahkarami||Giovanna Varricchio||Quentin Vermande||Ernest van Wijland. (2022) "Maximizing Nash Social Welfare in 2-Value Instances", Proceedings of the AAAI Conference on Artificial Intelligence, p.4760-4767

Hannaneh Akrami||Bhaskar Ray Chaudhury||Martin Hoefer||Kurt Mehlhorn||Marco Schmalhofer||Golnoosh Shahkarami||Giovanna Varricchio||Quentin Vermande||Ernest van Wijland, "Maximizing Nash Social Welfare in 2-Value Instances", AAAI, p.4760-4767, 2022.

Hannaneh Akrami||Bhaskar Ray Chaudhury||Martin Hoefer||Kurt Mehlhorn||Marco Schmalhofer||Golnoosh Shahkarami||Giovanna Varricchio||Quentin Vermande||Ernest van Wijland. "Maximizing Nash Social Welfare in 2-Value Instances". Proceedings of the AAAI Conference on Artificial Intelligence, 2022, p.4760-4767.

Hannaneh Akrami||Bhaskar Ray Chaudhury||Martin Hoefer||Kurt Mehlhorn||Marco Schmalhofer||Golnoosh Shahkarami||Giovanna Varricchio||Quentin Vermande||Ernest van Wijland. "Maximizing Nash Social Welfare in 2-Value Instances". Proceedings of the AAAI Conference on Artificial Intelligence, (2022): 4760-4767.

Hannaneh Akrami||Bhaskar Ray Chaudhury||Martin Hoefer||Kurt Mehlhorn||Marco Schmalhofer||Golnoosh Shahkarami||Giovanna Varricchio||Quentin Vermande||Ernest van Wijland. Maximizing Nash Social Welfare in 2-Value Instances. AAAI[Internet]. 2022[cited 2023]; 4760-4767.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking “Accept All”, you consent to the use of ALL the cookies. However, you may visit "Cookie Settings" to provide a controlled consent.
Cookie SettingsAccept All
Manage consent

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience.
Necessary
Always Enabled
Necessary cookies are absolutely essential for the website to function properly. These cookies ensure basic functionalities and security features of the website, anonymously.
CookieDurationDescription
cookielawinfo-checkbox-analytics11 monthsThis cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".
cookielawinfo-checkbox-functional11 monthsThe cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".
cookielawinfo-checkbox-necessary11 monthsThis cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".
cookielawinfo-checkbox-others11 monthsThis cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.
cookielawinfo-checkbox-performance11 monthsThis cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".
viewed_cookie_policy11 monthsThe cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data.
Functional
Functional cookies help to perform certain functionalities like sharing the content of the website on social media platforms, collect feedbacks, and other third-party features.
Performance
Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.
Analytics
Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc.
Advertisement
Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. These cookies track visitors across websites and collect information to provide customized ads.
Others
Other uncategorized cookies are those that are being analyzed and have not been classified into a category as yet.
SAVE & ACCEPT