Regret minimization in online Bayesian persuasion: Handling adversarial receiver's types under full and partial feedback models-Reference-Cited by-同舟云学术

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Regret minimization in online Bayesian persuasion: Handling adversarial receiver's types under full and partial feedback models

Published:2023-01 Issue: Volume:314 Page:103821
ISSN:0004-3702
Container-title:Artificial Intelligence
language:en
Short-container-title:Artificial Intelligence

Author:

Castiglioni Matteo^ORCID,Celli Andrea,Marchesi Alberto,Gatti Nicola^ORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics

Reference76 articles.

1. Online Bayesian persuasion;Castiglioni;Adv. Neural Inf. Process. Syst.,2020

2. Bayesian persuasion;Kamenica;Am. Econ. Rev.,2011

3. Targeting and signaling in ad auctions;Badanidiyuru,2018

4. Signaling schemes for revenue maximization;Emek;ACM Trans. Econ. Comput.,2014

5. Send mixed signals: earn more, work less;Bro Miltersen,2012

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1. No-Regret Learning in Bilateral Trade via Global Budget Balance;Proceedings of the 56th Annual ACM Symposium on Theory of Computing;2024-06-10

2. Reducing the Gap Between Theory and Applications in Algorithmic Bayesian Persuasion;SpringerBriefs in Applied Sciences and Technology;2024

3. Increasing revenue in Bayesian posted price auctions through signaling;Artificial Intelligence;2023-10

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