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Justin A. Mulvany

dblp:253/4042 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0003-2625-4511ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Theory of computation · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Algorithmic game theory and mechanism design · 100%
Network and information security
1 paper
Blockchain and cryptocurrency security · 77% Cryptographic protocols and secure computation · 23%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Blockchain and cryptocurrency security
smart contract
0.712023
Blockchain Mediated Persuasion · EC 2023
Algorithmic game theory and mechanism design › mechanism design › information design
bayesian persuasion
0.712023
Blockchain Mediated Persuasion · EC 2023
Algorithmic game theory and mechanism design › mechanism design
commitment
0.712023
Blockchain Mediated Persuasion · EC 2023
Cryptographic protocols and secure computation
commitment schemes
0.212023
Blockchain Mediated Persuasion · EC 2023

Methods — techniques the papers use, named apart from their topics

blockchain · 1.3bayesian persuasion · 1.3
YearPublicationVenuePosition
2023 Blockchain Mediated Persuasion
abstract
In the classic Bayesian Persuasion model studied by [Kamenica and Gentzkow, 2011], there are two players: the first, called Sender, wishes to persuade the second, called Receiver, to take a desired action. Provided that Sender is ex-post better informed about the underlying state of the world, Sender can leverage their informational advantage by communicating with Receiver via a signal mechanism. However, Sender's ability to effectively manage Receiver's beliefs largely hinges on the assumption that Sender can credibly commit to a signal mechanism. Usually, it is not ex-post optimal for Sender to follow the mechanism, but instead to deviate and send the message that generates the highest payoff. Consequently, Receiver may not have faith in Sender's ability to commit. In this case, all bets are off: persuasion devolves into cheap talk.
Kimon Drakopoulos, Irene Lo, Justin A. Mulvany
EC3