no code implementations • 23 May 2024 • Luise Ge, Daniel Halpern, Evi Micha, Ariel D. Procaccia, Itai Shapira, Yevgeniy Vorobeychik, Junlin Wu
The problem of learning a reward function is one of preference aggregation that, we argue, largely falls within the scope of social choice theory.
no code implementations • 16 Feb 2024 • Daniel Halpern, Safwan Hossain, Jamie Tucker-Foltz
Motivated by the difficulty of specifying complete ordinal preferences over a large set of $m$ candidates, we study voting rules that are computable by querying voters about $t < m$ candidates.
no code implementations • 2 Jul 2021 • Manon Revel, Tao Lin, Daniel Halpern
We analyze the optimal size of a congress in a representative democracy.
no code implementations • 20 May 2021 • Daniel Halpern, Nisarg Shah
We study the fundamental problem of allocating indivisible goods to agents with additive preferences.
no code implementations • 16 Apr 2020 • Vasilis Gkatzelis, Daniel Halpern, Nisarg Shah
We study the following metric distortion problem: there are two finite sets of points, $V$ and $C$, that lie in the same metric space, and our goal is to choose a point in $C$ whose total distance from the points in $V$ is as small as possible.