Better Reinforcement Learning for Human in the Loop Systems | Emma Brunskill | WiDS 2019

Emma Brunskill, Assistant Professor, Computer Science, Stanford University

There is increasing excitement about reinforcement learning– a subarea of machine learning for enabling an agent to learn to make good decisions. Yet numerous questions and challenges remain for reinforcement learning to help support progress in important high stakes domains like education, consumer marketing and healthcare. I’ll discuss some recent advances in these areas, and our work towards creating transparent, accountable reinforcement learning approaches that can interact beneficially with people.