Persuasion and Incentives Through the Lens of Duality

Shaddin Dughmi, Rad Niazadeh, Alexandros Psomas, S. Matthew Weinberg

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations


Lagrangian duality underlies both classical and modern mechanism design. In particular, the dual perspective often permits simple and detail-free characterizations of optimal and approximately optimal mechanisms. This paper applies this same methodology to a close cousin of traditional mechanism design, one which shares conceptual and technical elements with its more mature relative: the burgeoning field of persuasion. The dual perspective permits us to analyze optimal persuasion schemes both in settings which have been analyzed in prior work, as well as for natural generalizations which we are the first to explore in depth. Most notably, we permit combining persuasion policies with payments, which serve to augment the persuasion power of the scheme. In both single and multi-receiver settings, as well as under a variety of constraints on payments, we employ duality to obtain structural insights, as well as tractable and simple characterizations of optimal policies.

Original languageEnglish (US)
Title of host publicationWeb and Internet Economics - 15th International Conference, WINE 2019, Proceedings
EditorsIoannis Caragiannis, Vahab Mirrokni, Evdokia Nikolova
Number of pages14
ISBN (Print)9783030353889
StatePublished - 2019
Event15th Conference on Web and Internet Economics, WINE 2019 - New York City, United States
Duration: Dec 10 2019Dec 12 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11920 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference15th Conference on Web and Internet Economics, WINE 2019
Country/TerritoryUnited States
CityNew York City

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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