no code implementations • 27 May 2024 • Kanad Shrikar Pardeshi, Itai Shapira, Ariel D. Procaccia, Aarti Singh
We focus on two learning tasks; in the first, the input is vectors of utilities of an action (decision or policy) for individuals in a group and their associated social welfare as judged by a policy maker, whereas in the second, the input is pairwise comparisons between the welfares associated with a given pair of utility vectors.
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.
1 code implementation • 3 Sep 2023 • Sara Fish, Paul Gölz, David C. Parkes, Ariel D. Procaccia, Gili Rusak, Itai Shapira, Manuel Wüthrich
Traditionally, social choice theory has only been applicable to choices among a few predetermined alternatives but not to more complex decisions such as collectively selecting a textual statement.
no code implementations • 6 Mar 2023 • Itai Shapira
This study explores the number of neurons required for a Rectified Linear Unit (ReLU) neural network to approximate multivariate monomials.