Towards an Information Theoretic Framework of Context-Based Offline
Meta-Reinforcement Learning
Towards an Information Theoretic Framework of Context-Based Offline
Meta-Reinforcement Learning
As a marriage between offline RL and meta-RL, the advent of offline meta-reinforcement learning (OMRL) has shown great promise in enabling RL agents to multi-task and quickly adapt while acquiring knowledge safely. Among which, Context-based OMRL (COMRL) as a popular paradigm, aims to learn a universal policy conditioned on effective …