Hierarchical and Continual RL with Doina Precup - #567

Today we’re joined by Doina Precup, a research team lead at DeepMind Montreal, and a professor at McGill University. In our conversation with Doina, we discuss her recent research interests, including her work in hierarchical reinforcement learning, with the goal being agents learning abstract representations, especially over time. We also explore her work on reward specification for RL agents, where she hypothesizes that a reward signal in a complex environment could lead an agent to develop attributes of intuitive intelligence. …

continual hierarchical rl