Tighter guarantees for RL actor-critic training
Researchers prove that actor-critic RL algorithms stay on track with high probability, giving stronger theoretical safety guarantees.
Researchers prove that actor-critic RL algorithms stay on track with high probability, giving stronger theoretical safety guarantees.