216 citations · 321 across the 16 of their papers we have counts for
18 papers
CT-DQN: Control-Tutored Deep Reinforcement Learning
Francesco De Lellis, Marco Coraggio, Giovanni Russo +2
One of the major challenges in Deep Reinforcement Learning for control is the need for extensive training to learn the policy. Motivated by this, we present the design of the Contr…
External control of a genetic toggle switch via Reinforcement Learning
Sara Maria Brancato, Francesco De Lellis, Davide Salzano +2
We investigate the problem of using a learning-based strategy to stabilize a synthetic toggle switch via an external control approach. To overcome the data efficiency problem that…
Control-Tutored Reinforcement Learning: Towards the Integration of Data-Driven and Model-Based Control
F. De Lellis, M. Coraggio, G. Russo +2
We present an architecture where a feedback controller derived on an approximate model of the environment assists the learning process to enhance its data efficiency. This architec…
Utilizing synchronization to partition power networks into microgrids
Ricardo Cardona-Rivera, Francesco Lo Iudice, Antonio Grotta +2
The problem of partitioning a power grid into a set of microgrids, or islands, is of interest for both the design of future smart grids, and as a last resort to restore power dispa…
Leadership emergence in walking groups
Maria Lombardi, William H. Warren, M. di Bernardo
Understanding the mechanisms underlying the emergence of leadership in multi-agent systems is still under investigation in many areas of research where group coordination is involv…
Distributed Discontinuous Coupling for Convergence in Networks of Heterogeneous Nonlinear Systems
Marco Coraggio, Pietro DeLellis, Mario di Bernardo
Synchronization is a crucial phenomenon in many natural and artificial complex network systems. Applications include neuronal networks, formation control and coordination in roboti…