A note on the article "On Exploiting Spectral Properties for Solving MDP with Large State Space"

This provides a more robust theoretical foundation for a specific algorithm in reinforcement learning, but it is incremental as it builds directly on previous work.

The paper addresses the convergence of an existing algorithm for solving Markov Decision Processes with large state spaces, showing that it is guaranteed to converge under all conditions, improving upon prior theoretical results that relied on unrealistic assumptions.