Search Results for author:
Found 3 papers, 0 papers with code
Towards a Better Understanding of Learning with Multiagent Teams
While it has long been recognized that a team of individual learning agents can be greater than the sum of its parts, recent work has shown that larger teams are not necessarily more effective than smaller ones.
Learning to Learn Group Alignment: A Self-Tuning Credo Framework with Multiagent Teams
Mixed incentives among a population with multiagent teams has been shown to have advantages over a fully cooperative system; however, discovering the best mixture of incentives or team structure is a difficult and dynamic problem.
The Human Effect Requires Affect: Addressing Social-Psychological Factors of Climate Change with Machine Learning
Machine learning has the potential to aid in mitigating the human effects of climate change.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
