no code implementations • 20 Feb 2024 • Yuke Li, Guangyi Chen, Ben Abramowitz, Stefano Anzellott, Donglai Wei
Moreover, we validate that the learned temporal dynamic transition and temporal dynamic generation modules possess transferable qualities.
no code implementations • 18 Nov 2022 • Xiaolin Sun, Jacob Masur, Ben Abramowitz, Nicholas Mattei, Zizhan Zheng
We introduce a novel formal model of \emph{pandering}, or strategic preference reporting by candidates seeking to be elected, and examine the resilience of two democratic voting systems to pandering within a single round and across multiple rounds.
no code implementations • 15 Nov 2022 • Ben Abramowitz, Nicholas Mattei
Agents care not only about the outcomes of collective decisions but also about how decisions are made.
no code implementations • 15 Nov 2022 • Ben Abramowitz, Omer Lev, Nicholas Mattei
We consider the problem of determining a binary ground truth using advice from a group of independent reviewers (experts) who express their guess about a ground truth correctly with some independent probability (competence).
no code implementations • 3 Jun 2022 • Ben Abramowitz, Nicholas Mattei
While a full answer depends on the type of signal, correlation of signals, and desired output, a problem common to all of these applications is that of differentiating sources based on their quality and weighting them accordingly.
no code implementations • 5 Nov 2020 • Ben Abramowitz, Ehud Shapiro, Nimrod Talmon
Consider n agents forming an egalitarian, self-governed community.
Multiagent Systems
no code implementations • 25 Jun 2019 • Ben Abramowitz, Elliot Anshelevich, Wennan Zhu
Previous work has often assumed that only ordinal preferences of the voters are known (instead of their true costs), and focused on minimizing distortion: the quality of the chosen candidate as compared with the best possible candidate.