no code implementations • 30 Jan 2024 • Itai Arieli, Yakov Babichenko, Omer Madmon, Moshe Tennenholtz
We consider a model of third-degree price discrimination, in which the seller has a valuation for the product which is unknown to the market designer, who aims to maximize the buyers' surplus by revealing information regarding the buyer's valuation to the seller.
no code implementations • 15 Jul 2023 • Itai Arieli, Yakov Babichenko, Fedor Sandomirskiy
We consider a model of Bayesian persuasion with one informed sender and several uninformed receivers.
no code implementations • 11 Jul 2023 • Itai Arieli, Ivan Geffner, Moshe Tennenholtz
The payoff of the senders and of the receiver depend on both the state of the world and the action selected by the receiver.
no code implementations • 1 Feb 2023 • Itai Arieli, Ronen Gradwohl, Rann Smorodinsky
We study the robustness of cheap-talk equilibria to infinitesimal private information of the receiver in a model with a binary state-space and state-independent sender-preferences.
no code implementations • 26 Jan 2023 • Itai Arieli, Yakov Babichenko, Stephan Müller, Farzad Pourbabaee, Omer Tamuz
In a misspecified social learning setting, agents are condescending if they perceive their peers as having private information that is of lower quality than it is in reality.
no code implementations • 8 Mar 2022 • Itai Arieli, Yakov Babichenko, Fedor Sandomirskiy
For one mediator, the characterization has a geometric meaning of constrained concavification of sender's utility, optimal persuasion requires the same number of signals as without mediators, and the presence of the mediator is never profitable for the sender.
no code implementations • 23 Feb 2021 • Gideon Amir, Itai Arieli, Galit Ashkenazi-Golan, Ron Peretz
We study a model of opinion exchange in social networks where a state of the world is realized and every agent receives a zero-mean noisy signal of the realized state.
Probability Discrete Mathematics Social and Information Networks Physics and Society 91D30, 60C05
no code implementations • 8 Jan 2021 • Itai Arieli, Yakov Babichenko, Manuel Mueller-Frank
We analyze boundedly rational updating from aggregate statistics in a model with binary actions and binary states.
no code implementations • 10 Nov 2020 • Itai Arieli, Fedor Sandomirskiy, Rann Smorodinsky
We illustrate the power of the local learning requirement by constructing a family of social networks that guarantee information aggregation despite that no agent is a social hub (in other words, there are no opinion leaders).
no code implementations • 26 Feb 2020 • Itai Arieli, Yakov Babichenko, Fedor Sandomirskiy, Omer Tamuz
We study the set of possible joint posterior belief distributions of a group of agents who share a common prior regarding a binary state, and who observe some information structure.
