Antoine Clavaud

Squeezing More from the Stream : Learning Representation Online for Streaming Reinforcement Learning

In streaming Reinforcement Learning (RL), transitions are observed and discarded immediately after a single update. While this minimizes resource usage for on-device applications, it makes agents notoriously sample-inefficient, since value-based losses alone struggle to extract meaningful representa…