4 citations · 8 across the 5 of their papers we have counts for
5 papers
Data-driven architecture to encode information in the kinematics of robots and artificial avatars
Francesco De Lellis, Marco Coraggio, Nathan C. Foster +3
We present a data-driven control architecture for modifying the kinematics of robots and artificial avatars to encode specific information such as the presence or not of an emotion…
In vivo learning-based control of microbial populations density in bioreactors
Sara Maria Brancato, Davide Salzano, Francesco De Lellis +3
A key problem toward the use of microorganisms as bio-factories is reaching and maintaining cellular communities at a desired density and composition so that they can efficiently c…
Guaranteeing Control Requirements via Reward Shaping in Reinforcement Learning
Francesco De Lellis, Marco Coraggio, Giovanni Russo +2
In addressing control problems such as regulation and tracking through reinforcement learning, it is often required to guarantee that the acquired policy meets essential performanc…
Intermittent non-pharmaceutical strategies to mitigate the COVID-19 epidemic in a network model of Italy via constrained optimization
Marco Coraggio, Shihao Xie, Francesco De Lellis +2
This paper is concerned with the design of intermittent non-pharmaceutical strategies to mitigate the spread of the COVID-19 epidemic exploiting network epidemiological models. Spe…
Tutoring Reinforcement Learning via Feedback Control
Francesco De Lellis, Giovanni Russo, Mario di Bernardo
We introduce a control-tutored reinforcement learning (CTRL) algorithm. The idea is to enhance tabular learning algorithms by means of a control strategy with limited knowledge of…