Tag
Introduces QuantFPFlow, a reinforcement learning framework that uses quantum amplitude estimation to achieve a quadratic speedup in estimating the Fokker-Planck partition function for continuous control, improving exploration and avoiding local optima.
This article explains how incorporating Shannon entropy into reinforcement learning objectives creates more robust agents capable of handling unexpected or adversarial changes in rewards and dynamics.