This paper aims to introduce nonlinear optimization in the fuzzy reinforcement learning (RL)
approach through genetic algorithm (GA)-based minimization. In conventional fuzzy RL, an …

In this paper we propose a Lyapunov theory based Markov game fuzzy controller which is
both safe and stable. We attempt to optimize a reinforcement learning (RL) based controller …

Safety and robustness are two desired properties for any reinforcement learning algorithm.
Constrained Markov Decision Processes (CMDPs) can handle additional safety constraints …

El control de sistemas complejos se basa en resolver problemas en sistemas no lineales,
los cuales generalmente son inestables. Un ejemplo de dicho sistema es el robot de auto …

This work proposes Lyapunov theory based Fuzzy/Neural Reinforcement Learning (RL)
controllers with guaranteed stability. We look at ways in which Lyapunov theory could be …

The problem of controlling a robotic goalkeeper to intercept a soccer ball is studied within
the context of the direct Lyapunov theory. The rotational dynamics of the goalkeeper body is …

In this paper, a novel Adaptive control technique is proposed to stabilize the linear inverted
pendulum at upright position. Adaptive Backstepping is a Lyapunov Based robust control …

In this paper we propose a game theoretic Lyapunov fuzzy controller which is both safe and
stable. We attempt to optimize a reinforcement learning based controller using Markov …

This paper aims at designing a novel Hybrid Lyapunov theory based Fuzzy Reinforcement
Learning Controller with guaranteed stability for non linear systems. One of the major …

Rekursive und passivitätsbasierte Regelungen zur Neigwinkelstabilisierung eines Segway
Modells Page 1 Eingereicht von Daniel Brunner Angefertigt am Institut für Robotik Betreuer …