MAD: A Magnitude And Direction Policy Parametrization for Stability Constrained Reinforcement Learning

Luca Furieri, Sucheth Shenoy, Danilo Saccani +2

We introduce magnitude and direction (MAD) policies, a policy parameterization for reinforcement learning (RL) that preserves Lp closed-loop stability for nonlinear dynamical syste…