M. Khaniki

Safe and adaptive control of non-stationary stochastic systems via Lyapunov-constrained distributional reinforcement learning

Simulations in chaotic and hyperchaotic systems showcase LG-DRL-ER’s superior performance in achieving stable, adaptive control compared to existing methods, and establishes finite-time convergence guarantees with explicit bounds on the convergence time.