Model-free Representation Learning and Exploration in Low-rank MDPs. (arXiv:2102.07035v2 [cs.LG] UPDATED)

The low rank MDP has emerged as an important model for studying
representation learning and exploration in reinforcement learning. With a known
representation, several model-free exploration strategies exist. In contrast,
all algorithms for the unknown representation setting are model-based, thereby
requiring the ability to model the full dynamics. In this work, we present the
first model-free representation learning algorithms for low rank MDPs. The key
algorithmic contribution is a new minimax representation learning objective,
for which we provide variants with …

arxiv exploration free learning lg representation representation learning