4 citations · 9 across the 18 of their papers we have counts for
3 papers · 1 filter
A stabilizing reinforcement learning approach for sampled systems with partially unknown models
Lukas Beckenbach, Pavel Osinenko, Stefan Streif
Reinforcement learning is commonly associated with training of reward-maximizing (or cost-minimizing) agents, in other words, controllers. It can be applied in model-free or model-…
A framework for online, stabilizing reinforcement learning
Grigory Yaremenko, Georgiy Malaniya, Pavel Osinenko
Online reinforcement learning is concerned with training an agent on-the-fly via dynamic interaction with the environment. Here, due to the specifics of the application, it is not…
On stochastic stabilization via non-smooth control Lyapunov functions
Pavel Osinenko, Grigory Yaremenko, Georgiy Malaniya
Control Lyapunov function is a central tool in stabilization. It generalizes an abstract energy function -- a Lyapunov function -- to the case of controlled systems. It is a known…