3 papers
cs.RO2024
A novel agent with formal goal-reaching guarantees: an experimental study with a mobile robot
Grigory Yaremenko, Dmitrii Dobriborsci, Roman Zashchitin +3
Reinforcement Learning (RL) has been shown to be effective and convenient for a number of tasks in robotics. However, it requires the exploration of a sufficiently large number of…
cs.RO2024
Critic as Lyapunov function (CALF): a model-free, stability-ensuring agent
Pavel Osinenko, Grigory Yaremenko, Roman Zashchitin +3
This work presents and showcases a novel reinforcement learning agent called Critic As Lyapunov Function (CALF) which is model-free and ensures online environment, in other words,…
math.OC2021
A study of first-passage time minimization via Q-learning in heated gridworlds
M. A. Larchenko, P. Osinenko, G. Yaremenko +1
Optimization of first-passage times is required in applications ranging from nanobots navigation to market trading. In such settings, one often encounters unevenly distributed nois…