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DOI: 10.4230/LIPIcs.FORC.2025.21

OWA for Bipartite Assignments

Authors: Jabari Hastings, Sigal Oren, and Omer Reingold

Published in: LIPIcs, Volume 329, 6th Symposium on Foundations of Responsible Computing (FORC 2025)

Abstract

In resource allocation problems, a central planner often strives to have a fair assignment. A challenge they might face, however, is that there are several objectives that could be argued to be fair, such as the max-min and maximum social welfare. In this work, we study bipartite assignment problems involving the optimization of a class of functions that is sensitive to the relative utilities derived by individuals in allocation and captures these traditional objectives. We introduce and study a subclass of evaluation functions that targets the average welfare attained within some interval of the economic ladder (e.g., the bottom 10%, middle 50%, or top 80%). We provide an efficient algorithm that can be used to optimize the welfare for an arbitrary interval and also show how the approach can be used to approximate more general evaluation functions. We also study a subclass of evaluation functions consisting of the "fair" ordered weighted averages (OWA) introduced by Lesca et al. (Algorithmica 2019), which are most sensitive to the utilities received by the worst-off individuals. We provide a simple proof that optimizing this objective belongs to the class XP.

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Jabari Hastings, Sigal Oren, and Omer Reingold. OWA for Bipartite Assignments. In 6th Symposium on Foundations of Responsible Computing (FORC 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 329, pp. 21:1-21:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{hastings_et_al:LIPIcs.FORC.2025.21,
  author =	{Hastings, Jabari and Oren, Sigal and Reingold, Omer},
  title =	{{OWA for Bipartite Assignments}},
  booktitle =	{6th Symposium on Foundations of Responsible Computing (FORC 2025)},
  pages =	{21:1--21:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-367-6},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{329},
  editor =	{Bun, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FORC.2025.21},
  URN =		{urn:nbn:de:0030-drops-231482},
  doi =		{10.4230/LIPIcs.FORC.2025.21},
  annote =	{Keywords: fairness, matchings, approximation algorithms}
}

Document

DOI: 10.4230/DagRep.12.11.28

Computational Social Dynamics (Dagstuhl Seminar 22452)

Authors: Martin Hoefer, Sigal Oren, Roger Wattenhofer, and Giovanna Varricchio

Published in: Dagstuhl Reports, Volume 12, Issue 11 (2023)

Abstract

This report documents the program and outcomes of Dagstuhl Seminar 22452 "Computational Social Dynamics". The seminar addressed social and dynamic problems in the field of algorithmic game theory, and their implications in numerous applications, such as fair division, financial networks, or behavioral game theory. We summarize organizational aspects of the seminar, the talk abstracts, and the problems that were discussed in the open problem sessions.

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Martin Hoefer, Sigal Oren, Roger Wattenhofer, and Giovanna Varricchio. Computational Social Dynamics (Dagstuhl Seminar 22452). In Dagstuhl Reports, Volume 12, Issue 11, pp. 28-44, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{hoefer_et_al:DagRep.12.11.28,
  author =	{Hoefer, Martin and Oren, Sigal and Wattenhofer, Roger and Varricchio, Giovanna},
  title =	{{Computational Social Dynamics (Dagstuhl Seminar 22452)}},
  pages =	{28--44},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{12},
  number =	{11},
  editor =	{Hoefer, Martin and Oren, Sigal and Wattenhofer, Roger and Varricchio, Giovanna},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.12.11.28},
  URN =		{urn:nbn:de:0030-drops-178346},
  doi =		{10.4230/DagRep.12.11.28},
  annote =	{Keywords: algorithmic game theory, behavioral economics, fair division, financial networks, social networks}
}

Document

DOI: 10.4230/LIPIcs.ITCS.2022.55

Mechanism Design with Moral Bidders

Authors: Shahar Dobzinski and Sigal Oren

Published in: LIPIcs, Volume 215, 13th Innovations in Theoretical Computer Science Conference (ITCS 2022)

Abstract

A rapidly growing literature on lying in behavioral economics and psychology shows that individuals often do not lie even when lying maximizes their utility. In this work, we attempt to incorporate these findings into the theory of mechanism design. We consider players that have a preference for truth-telling and will only lie if their benefit from lying is sufficiently larger than the loss of the others. To accommodate such players, we introduce α-moral mechanisms, in which the gain of a player from misreporting his true value, comparing to truth-telling, is at most α times the loss that the others incur due to misreporting. Note that a 0-moral mechanism is a truthful mechanism. We develop a theory of moral mechanisms in the canonical setting of single-item auctions within the "reasonable" range of α, 0 ≤ α ≤ 1. We identify similarities and disparities to the standard theory of truthful mechanisms. In particular, we show that the allocation function does not uniquely determine the payments and is unlikely to admit a simple characterization. In contrast, recall that monotonicity characterizes the allocation function of truthful mechanisms. Our main technical effort is invested in determining whether the auctioneer can exploit the preference for truth-telling of the players to extract more revenue comparing to truthful mechanisms. We show that the auctioneer can indeed extract more revenue when the values of the players are correlated, even when there are only two players. However, we show that truthful mechanisms are revenue-maximizing even among moral ones when the values of the players are independently drawn from certain identical distributions (e.g., the uniform and exponential distributions). A by-product of our proof that optimal moral mechanisms are truthful is an alternative proof to Myerson’s optimal truthful mechanism characterization in the settings that we consider. We flesh out this approach by providing an alternative proof that does not involve moral mechanisms to Myerson’s characterization of optimal truthful mechanisms to all settings in which the values are independently drawn from regular distributions (not necessarily identical).

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Shahar Dobzinski and Sigal Oren. Mechanism Design with Moral Bidders. In 13th Innovations in Theoretical Computer Science Conference (ITCS 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 215, pp. 55:1-55:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{dobzinski_et_al:LIPIcs.ITCS.2022.55,
  author =	{Dobzinski, Shahar and Oren, Sigal},
  title =	{{Mechanism Design with Moral Bidders}},
  booktitle =	{13th Innovations in Theoretical Computer Science Conference (ITCS 2022)},
  pages =	{55:1--55:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-217-4},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{215},
  editor =	{Braverman, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2022.55},
  URN =		{urn:nbn:de:0030-drops-156513},
  doi =		{10.4230/LIPIcs.ITCS.2022.55},
  annote =	{Keywords: Mechanism Design, Cognitive Biases, Revenue Maximization}
}

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Documents authored by Oren, Sigal

OWA for Bipartite Assignments

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Computational Social Dynamics (Dagstuhl Seminar 22452)

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Mechanism Design with Moral Bidders

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