all AI news
Learning to Manipulate under Limited Information
April 17, 2024, 4:43 a.m. | Wesley H. Holliday, Alexander Kristoffersen, Eric Pacuit
cs.LG updates on arXiv.org arxiv.org
Abstract: By classic results in social choice theory, any reasonable preferential voting method sometimes gives individuals an incentive to report an insincere preference. The extent to which different voting methods are more or less resistant to such strategic manipulation has become a key consideration for comparing voting methods. Here we measure resistance to manipulation by whether neural networks of varying sizes can learn to profitably manipulate a given voting method in expectation, given different types of …
abstract arxiv become cs.ai cs.gt cs.lg cs.ma econ.th information key manipulation report results social theory type voting
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
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
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Business Intelligence Manager
@ Sanofi | Budapest
Principal Engineer, Data (Hybrid)
@ Homebase | Toronto, Ontario, Canada