Invariant Policy Optimization: Towards Stronger Generalization in Reinforcement Learning

1 code implementation • 1 Jun 2020 • Anoopkumar Sonar, Vincent Pacelli, Anirudha Majumdar

A fundamental challenge in reinforcement learning is to learn policies that generalize beyond the operating domains experienced during training.

Policy Gradient Methods reinforcement-learning +1

PAC-Bayes Control: Learning Policies that Provably Generalize to Novel Environments

1 code implementation • 11 Jun 2018 • Anirudha Majumdar, Alec Farid, Anoopkumar Sonar

The key technical idea behind our approach is to leverage tools from generalization theory in machine learning by exploiting a precise analogy (which we present in the form of a reduction) between generalization of control policies to novel environments and generalization of hypotheses in the supervised learning setting.