124 citations · 465 across the 54 of their papers we have counts for
57 papers
Safe Leader-Follower Density Control via Higher-Order Mean-Field Control Barrier Functions
Cinzia Tomaselli, Mario di Bernardo
Mean-field control barrier functions (MF-CBFs) enforce safety of large-scale multi-agent systems at the level of densities, but existing formulations require the control to act dir…
Entropy-Regularized Optimal Transport for Time-Varying Multi-Agent Coverage Control
Italo Napolitano, Mario di Bernardo
This paper addresses time-varying coverage control for multi-agent systems, formulated as the tracking of an evolving target density via entropy-regularized semi-discrete optimal t…
Synchronization of directed hypergraphs with heterogeneities via dynamic coupling
Aiwin Thomas Vadakkan, Pietro De Lellis, Mario di Bernardo
Many real-world networks involve interactions among three or more agents that cannot be reduced to pairwise coupling, making hypergraphs a natural modeling framework. In this work,…
Memorial for Dr. Erik Bollt
Scott Bollt, Mario di Bernardo, Jeremie Fish +4
In this paper, we give a memorial tribute to Prof. Erik M. Bollt (1967--2025).
Feedback Control of a Recirculating Bioreactor with Electrophoretic Removal of Inhibitory Extracellular DNA
Antonio Spallone, Davide Fiore, Fabrizio Cartenì +1
Extracellular DNA accumulation in recirculating bioprocesses inhibits microbial growth and reduces productivity. We consider a continuous bioreactor with a recirculating loop and a…
Multi-Scale Control of Large Agent Populations: From Density Dynamics to Individual Actuation
Mario di Bernardo
We review a body of recent work by the author and collaborators on controlling the spatial organisation of large agent populations across multiple scales. A central theme is the sy…
Semi-discrete Optimal Transport for Time-Varying Multi-Agent Coverage Control
Italo Napolitano, Mario di Bernardo
Coverage control algorithms have traditionally focused on static target densities, where agents optimally cover a fixed spatial distribution. However, many applications, such as en…
Learning-based cognitive architecture for enhancing coordination in human groups
Antonio Grotta, Marco Coraggio, Antonio Spallone +2
As interactions with autonomous agents-ranging from robots in physical settings to avatars in virtual and augmented realities-become more prevalent, developing advanced cognitive a…
Leader-Follower Density Control of Spatial Dynamics in Large-Scale Multi-Agent Systems
Gian Carlo Maffettone, Alain Boldini, Maurizio Porfiri +1
We address the problem of controlling the density of a large ensemble of follower agents by acting on a group of leader agents that interact with them. Using coupled partial integr…
High-dimensional continuification control of large-scale multi-agent systems under limited sensing and perturbations
Gian Carlo Maffettone, Mario di Bernardo, Maurizio Porfiri
This paper investigates the robustness of a novel high-dimensional continuification control method for complex multi-agent systems. We begin by formulating a partial differential e…
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…
Mixed Reality Environment and High-Dimensional Continuification Control for Swarm Robotics
Gian Carlo Maffettone, Lorenzo Liguori, Eduardo Palermo +2
Many new methodologies for the control of large-scale multi-agent systems are based on macroscopic representations of the emerging system dynamics, in the form of continuum approxi…
Data-driven design of complex network structures to promote synchronization
Marco Coraggio, Mario di Bernardo
We consider the problem of optimizing the interconnection graphs of complex networks to promote synchronization. When traditional optimization methods are inapplicable, due to unce…
Shepherding control and herdability in complex multiagent systems
Andrea Lama, Mario di Bernardo
We study the shepherding control problem where a group of "herders" need to orchestrate their collective behaviour in order to steer the dynamics of a group of "target" agents towa…
Preliminary results on the herdability of complex multiagent systems via local information
Andrea Lama, Mario Di Bernardo
We present preliminary results on the problem of driving the dynamics of a group of agents, the herders, so as to steer the collective behaviour of another group of agents, the tar…
Continuification control of large-scale multiagent systems under limited sensing and structural perturbations
Gian Carlo Maffettone, Maurizio Porfiri, Mario di Bernardo
We investigate the stability and robustness properties of a continuification-based strategy for the control of large-scale multiagent systems. Within continuation-based strategy, o…
Local convergence of multi-agent systems towards triangular patterns
Andrea Giusti, Marco Coraggio, Mario di Bernardo
Geometric pattern formation is an important emergent behavior in many applications involving large-scale multi-agent systems, such as sensor networks deployment and collective tran…
Consensus-based Distributed Intentional Controlled Islanding of Power Grids
Francesco Lo Iudice, Ricardo Cardona-Rivera, Antonio Grotta +2
The problem of partitioning a power grid into a set of islands can be a solution to restore power dispatchment in sections of a grid affected by an extreme failure. Current solutio…
Continuification-based control of large multiagent systems in a ring
Gian Carlo Maffettone, Alain Boldini, Mario di Bernardo +1
In this paper, we propose a method to control large-scale multiagent systems swarming in a ring. Specifically, we use a continuification-based approach that transforms the microsco…
Distributed control for geometric pattern formation of large-scale multirobot systems
Andrea Giusti, Gian Carlo Maffettone, Davide Fiore +2
Geometric pattern formation is crucial in many tasks involving large-scale multi-agent systems. Examples include mobile agents performing surveillance, swarm of drones or robots, o…
Predicting and Understanding Human Action Decisions during Skillful Joint-Action via Machine Learning and Explainable-AI
Fabrizia Auletta, Rachel W. Kallen, Mario di Bernardo +1
This study uses supervised machine learning (SML) and explainable artificial intelligence (AI) to model, predict and understand human decision-making during skillful joint-action.…
Minimax Flow over Acyclic Networks: Distributed Algorithms and Microgrid Application
Marco Coraggio, Saber Jafarpour, Francesco Bullo +1
Given a flow network with variable suppliers and fixed consumers, the minimax flow problem consists in minimizing the maximum flow between nodes, subject to flow conservation and c…