Add to ORKGCover: Saturated policy for the pendulum swing-up problem as learned by the model learning actor-critic algorithm, approximated using a network of radial basis functions
International audienceReinforcement learning (RL) is generally considered as the machine learning an...
International audienceReinforcement learning (RL) is generally considered as the machine learning an...
Online Reinforcement Learning is a possible solution for adaptive nonlinear flight control. In this ...
Classical control theory requires a model to be derived for a system, before any control design can ...
Classical control theory requires a model to be derived for a system, before any control design can ...
This work extends and compares some recent model+learning-based methodologies for optimal control wi...
This paper focuses on the efficiency improvement of online actor-critic design base on the Levenberg...
The reinforcement learning (RL) framework enables to construct controllers that try to find find an ...
In this article, we propose a new reinforcement learning (RL) method based on an actor-critic archit...
Abstract—Policy gradient based actor-critic algorithms are amongst the most popular algorithms in th...
Over the last couple of decades the demand for high precision and enhanced performance of physical s...
Inverted pendulums have been classic setups in the control laboratories since the 1950s. They were o...
Abstract — In this paper we introduce an online algorithm that uses integral reinforcement knowledge...
Over the last couple of decades the demand for high precision and enhanced performance of physical s...
Actor-critic (AC) methods were among the earliest to be investigated in reinforcement learning (RL)....
International audienceReinforcement learning (RL) is generally considered as the machine learning an...
International audienceReinforcement learning (RL) is generally considered as the machine learning an...
Online Reinforcement Learning is a possible solution for adaptive nonlinear flight control. In this ...
Classical control theory requires a model to be derived for a system, before any control design can ...
Classical control theory requires a model to be derived for a system, before any control design can ...
This work extends and compares some recent model+learning-based methodologies for optimal control wi...
This paper focuses on the efficiency improvement of online actor-critic design base on the Levenberg...
The reinforcement learning (RL) framework enables to construct controllers that try to find find an ...
In this article, we propose a new reinforcement learning (RL) method based on an actor-critic archit...
Abstract—Policy gradient based actor-critic algorithms are amongst the most popular algorithms in th...
Over the last couple of decades the demand for high precision and enhanced performance of physical s...
Inverted pendulums have been classic setups in the control laboratories since the 1950s. They were o...
Abstract — In this paper we introduce an online algorithm that uses integral reinforcement knowledge...
Over the last couple of decades the demand for high precision and enhanced performance of physical s...
Actor-critic (AC) methods were among the earliest to be investigated in reinforcement learning (RL)....
International audienceReinforcement learning (RL) is generally considered as the machine learning an...
International audienceReinforcement learning (RL) is generally considered as the machine learning an...
Online Reinforcement Learning is a possible solution for adaptive nonlinear flight control. In this ...