Aug. 31, 2022, 1:10 a.m. | Meena Jagadeesan, Michael I. Jordan, Nika Haghtalab

cs.LG updates on arXiv.org arxiv.org

Competition between traditional platforms is known to improve user utility by
aligning the platform's actions with user preferences. But to what extent is
alignment exhibited in data-driven marketplaces? To study this question from a
theoretical perspective, we introduce a duopoly market where platform actions
are bandit algorithms and the two platforms compete for user participation. A
salient feature of this market is that the quality of recommendations depends
on both the bandit algorithm and the amount of data provided by …

alignment arxiv competition digital equilibria marketplaces

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne