research
∙
04/26/2023
Reinforcement Learning with Partial Parametric Model Knowledge
We adapt reinforcement learning (RL) methods for continuous control to b...
share
research
∙
04/07/2023
A modular framework for stabilizing deep reinforcement learning control
We propose a framework for the design of feedback controllers that combi...
research
∙
09/19/2022
Meta-Reinforcement Learning for Adaptive Control of Second Order Systems
Meta-learning is a branch of machine learning which aims to synthesize d...
research
∙
03/17/2022
Meta Reinforcement Learning for Adaptive Control: An Offline Approach
Meta-learning is a branch of machine learning which trains neural networ...
research
∙
11/13/2021
Deep Reinforcement Learning with Shallow Controllers: An Experimental Application to PID Tuning
Deep reinforcement learning (RL) is an optimization-driven framework for...
research
∙
03/26/2021
Almost Surely Stable Deep Dynamics
We introduce a method for learning provably stable deep neural network b...
research
∙
03/25/2021
A Meta-Reinforcement Learning Approach to Process Control
Meta-learning is a branch of machine learning which aims to quickly adap...
research
∙
05/10/2020
Optimal PID and Antiwindup Control Design as a Reinforcement Learning Problem
Deep reinforcement learning (DRL) has seen several successful applicatio...
research
∙
05/10/2020
