Understanding Self-Predictive Learning for Reinforcement Learning
The paper addresses self-predictive learning in reinforcement learning, which often fails by collapsing representations to trivial solutions. The authors propose bidirectional self-predictive learning, using coupled ODEs and two representations, to ensure non-collapse. This method leverages spectral decomposition on the state transition matrix to learn meaningful features.