Emma Brunskill: 2017 Plenary Session

 

Tuesday, April 11, 2017
Location: McCaw Hall, Arrillaga Alumni Center

"Reinforcement Learning and Education"

3:30PM

Abstract:

Reinforcement learning has the potential to help both agents and people. I work on algorithms and theory to advance reinforcement learning to benefit society, with a focus on using RL to improve human learning. I will discuss our work on off policy, policy evaluation: the counterfactual reasoning question around using data collected using some behavior policy to evaluate what it would be like to use a different policy in the future. This has wide applicability to online educational system, healthcare, robotics, consumer marketing and any domain in which it is expensive or logistically challenging to deploy new strategies.


Bio:

Emma Brunskill is an assistant professor of computer science at Stanford. She is a Rhodes Scholar, a Microsoft Faculty Fellow, a NSF CAREER awardee and a ONR Young Investigator Program recipient. Her work focused on interactive machine learning and reinforcement learning to improve society.