License: Creative Commons Attribution 3.0 Unported license (CC-BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CONCUR.2020.4
URN: urn:nbn:de:0030-drops-128167
URL: https://drops.dagstuhl.de/opus/volltexte/2020/12816/
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Palamidessi, Catuscia ; Romanelli, Marco

Modern Applications of Game-Theoretic Principles (Invited Paper)

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LIPIcs-CONCUR-2020-4.pdf (22 MB)


Abstract

Game theory is the study of the strategic behavior of rational decision makers who are aware that their decisions affect one another. Its simple but universal principles have found applications in the most diverse disciplines, including economics, social sciences, evolutionary biology, as well as logic, system science and computer science. Despite its long-standing tradition and its many advances, game theory is still a young and developing science. In this paper, we describe some recent and exciting applications in the fields of machine learning and privacy.

BibTeX - Entry

@InProceedings{palamidessi_et_al:LIPIcs:2020:12816,
  author =	{Catuscia Palamidessi and Marco Romanelli},
  title =	{{Modern Applications of Game-Theoretic Principles (Invited Paper)}},
  booktitle =	{31st International Conference on Concurrency Theory (CONCUR 2020)},
  pages =	{4:1--4:9},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-160-3},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{171},
  editor =	{Igor Konnov and Laura Kov{\'a}cs},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/12816},
  URN =		{urn:nbn:de:0030-drops-128167},
  doi =		{10.4230/LIPIcs.CONCUR.2020.4},
  annote =	{Keywords: Game theory, machine learning, privacy, security}
}

Keywords: Game theory, machine learning, privacy, security
Collection: 31st International Conference on Concurrency Theory (CONCUR 2020)
Issue Date: 2020
Date of publication: 26.08.2020


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