no code implementations • 25 May 2019 • Omer Ben-Porat, Fedor Sandomirskiy, Moshe Tennenholtz
In this family, we characterize conditions under which the fairness constraint helps the disadvantaged group.
no code implementations • 14 Jun 2020 • Reshef Meir, Fedor Sandomirskiy, Moshe Tennenholtz
We show that a k-sortition (a random committee of k voters with the majority vote within the committee) leads to an outcome within the factor 1+O(1/k) of the optimal social cost for any number of voters n, any number of issues $m$, and any preference profile.
1 code implementation • 5 Aug 2019 • Fedor Sandomirskiy, Erel Segal-haLevi
We show that, for a generic instance of the problem (all instances except a zero-measure set of degenerate problems), a fair fractionally Pareto-optimal division with the smallest possible number of shared objects can be found in polynomial time, assuming that the number of agents is fixed.
Computer Science and Game Theory Theoretical Economics
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.
no code implementations • 29 Dec 2021 • Kevin He, Fedor Sandomirskiy, Omer Tamuz
A private private information structure delivers information about an unknown state while preserving privacy: An agent's signal contains information about the state but remains independent of others' sensitive or private information.
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 • 14 Mar 2022 • Alexander V. Kolesnikov, Fedor Sandomirskiy, Aleh Tsyvinski, Alexander P. Zimin
We consider the problem of revenue-maximizing Bayesian auction design with several bidders having independent private values over several items.
no code implementations • 12 Mar 2022 • Federico Echenique, Joseph Root, Fedor Sandomirskiy
We study efficiency in general collective choice problems where agents have ordinal preferences and randomization is allowed.
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 • 8 Dec 2023 • Fedor Sandomirskiy, Omer Tamuz
Each decision is modeled as a menu of actions with outcomes, and a stochastic choice rule assigns probabilities to actions based on the outcome profile.
no code implementations • 20 Feb 2024 • Federico Echenique, Joseph Root, Fedor Sandomirskiy
We study matching markets with aligned preferences and establish a connection between common design objectives -- stability, efficiency, and fairness -- and the theory of optimal transport.