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Invited Talk
Sequential Decision Making With Information Asymmetry (Invited Talk)

Authors: Jiarui Gan, Rupak Majumdar, Goran Radanovic, and Adish Singla

Published in: LIPIcs, Volume 243, 33rd International Conference on Concurrency Theory (CONCUR 2022)


Abstract
We survey some recent results in sequential decision making under uncertainty, where there is an information asymmetry among the decision-makers. We consider two versions of the problem: persuasion and mechanism design. In persuasion, a more-informed principal influences the actions of a less-informed agent by signaling information. In mechanism design, a less-informed principal incentivizes a more-informed agent to reveal information by committing to a mechanism, so that the principal can make more informed decisions. We define Markov persuasion processes and Markov mechanism processes that model persuasion and mechanism design into dynamic models. Then we survey results on optimal persuasion and optimal mechanism design on myopic and far-sighted agents. These problems are solvable in polynomial time for myopic agents but hard for far-sighted agents.

Cite as

Jiarui Gan, Rupak Majumdar, Goran Radanovic, and Adish Singla. Sequential Decision Making With Information Asymmetry (Invited Talk). In 33rd International Conference on Concurrency Theory (CONCUR 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 243, pp. 4:1-4:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@InProceedings{gan_et_al:LIPIcs.CONCUR.2022.4,
  author =	{Gan, Jiarui and Majumdar, Rupak and Radanovic, Goran and Singla, Adish},
  title =	{{Sequential Decision Making With Information Asymmetry}},
  booktitle =	{33rd International Conference on Concurrency Theory (CONCUR 2022)},
  pages =	{4:1--4:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-246-4},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{243},
  editor =	{Klin, Bartek and Lasota, S{\l}awomir and Muscholl, Anca},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2022.4},
  URN =		{urn:nbn:de:0030-drops-170673},
  doi =		{10.4230/LIPIcs.CONCUR.2022.4},
  annote =	{Keywords: Bayesian persuasion, Automated mechanism design, Markov persuasion processes, Markov mechanism processes, Myopic agents}
}
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