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Documents authored by Gilboa, Matan


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Track A: Algorithms, Complexity and Games
A Characterization of Complexity in Public Goods Games

Authors: Matan Gilboa

Published in: LIPIcs, Volume 297, 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)


Abstract
We complete the characterization of the computational complexity of equilibrium in public goods games on graphs. In this model, each vertex represents an agent deciding whether to produce a public good, with utility defined by a "best-response pattern" determining the best response to any number of productive neighbors. We prove that the equilibrium problem is NP-complete for every finite non-monotone best-response pattern. This answers the open problem of [Gilboa and Nisan, 2022], and completes the answer to a question raised by [Papadimitriou and Peng, 2021], for all finite best-response patterns.

Cite as

Matan Gilboa. A Characterization of Complexity in Public Goods Games. In 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 297, pp. 73:1-73:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@InProceedings{gilboa:LIPIcs.ICALP.2024.73,
  author =	{Gilboa, Matan},
  title =	{{A Characterization of Complexity in Public Goods Games}},
  booktitle =	{51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)},
  pages =	{73:1--73:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-322-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{297},
  editor =	{Bringmann, Karl and Grohe, Martin and Puppis, Gabriele and Svensson, Ola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2024.73},
  URN =		{urn:nbn:de:0030-drops-202164},
  doi =		{10.4230/LIPIcs.ICALP.2024.73},
  annote =	{Keywords: Nash Equilibrium, Public Goods, Computational Complexity}
}
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