Jan Peters

Rollout Total Correlation for Deep Reinforcement Learning

This paper investigates how to learn representations by maximizing the rollout total correlation, the correlation among all learned representations and actions within the trajectories produced by the agent, and proposes an intrinsic reward based on the learned representation for better exploration.