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20212025
most citedAn experimental study of two predictive reinforcement learning methods and comparison with model-predictive control

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math.DS2025

Some remarks on stochastic converse Lyapunov theorems

Pavel Osinenko, Grigory Yaremenko

In this brief note, we investigate some constructions of Lyapunov functions for stochastic discrete-time stabilizable dynamical systems, in other words, controlled Markov chains. T…

math.DS2021

Effects of sampling and horizon in predictive reinforcement learning

Pavel Osinenko, Dmitrii Dobriborsci

Plain reinforcement learning (RL) may be prone to loss of convergence, constraint violation, unexpected performance, etc. Commonly, RL agents undergo extensive learning stages to a…