I am an M.S./Ph.D. student in the Autonomous Learning Lab at the University of Massachusetts, where Phil Thomas advises me. I study ways to ensure safety and fairness in reinforcement learning and bandits. Specifically, I am interested in designing (practical) machine learning algorithms with guarantees on behavior and performance.
Before attending UMass, I was a member of the Force Projection Sector at APL. I completed my undergraduate degree in Computer Science from the University of Maryland Baltimore County, where I also competed as a track & field athlete. Throughout my undergraduate career, I was mentored by Marie desJardins and coach David Bobb.
Contact information: bmetevier [at] umass [dot] edu
Reinforcement Learning When All Actions are Not Always Available
Yash Chandak, Georgios Theocharous, Blossom Metevier, Philip S. Thomas
Thirty-fourth Conference on Artificial Intelligence (AAAI 2020)
Abstract | Arxiv
Offline Contextual Bandits with High Probability Fairness Guarantees
Blossom Metevier, Stephen Giguere, Sarah Brockman, Ari Kobren, Yuriy Brun, Emma Brunskill, Philip S. Thomas
Advances in Neural Information Processing Systems (NeurIPs 2019)