Daniel J. Mankowitz

RL Unplugged: Benchmarks for Offline Reinforcement Learning.

2020 · arXiv (Cornell University)

Offline methods for reinforcement learning have a potential to help bridge the gap between reinforcement learning research and real-world applications. They make it possible to learn policies from offline datasets, thus overcoming concerns associated with …

Bootstrapping Skills

2015 · arXiv (Cornell University)

The monolithic approach to policy representation in Markov Decision Processes (MDPs) looks for a single policy that can be represented as a function from states to actions. For the monolithic approach to succeed (and this …