12 citations · 12 across the 5 of their papers we have counts for
5 papers
A bioreactor-based architecture for in vivo model-based and sim-to-real learning control of microbial consortium composition
Sara Maria Brancato, Davide Salzano, Davide Fiore +3
Microbial consortia offer significant biotechnological advantages over monocultures for bioproduction. However, industrial deployment is hampered by the lack of scalable architectu…
Sparse shepherding control of large-scale multi-agent systems via Reinforcement Learning
Luigi Catello, Italo Napolitano, Davide Salzano +1
We propose a Reinforcement Learning framework for sparse indirect control of large-scale multi-agent systems, where few controlled agents shape the collective behavior of many unco…
Bio-inspired density control of multi-agent swarms via leader-follower plasticity
Gian Carlo Maffettone, Alain Boldini, Mario di Bernardo +1
The design of control systems for the spatial self-organization of mobile agents is an open challenge across several engineering domains, including swarm robotics and synthetic bio…
Nonreciprocal field theory for decision-making in multi-agent control systems
Andrea Lama, Mario di Bernardo, Sabine H. L. Klapp
Field theories for complex systems traditionally focus on collective behaviors emerging from simple, reciprocal pairwise interaction rules. However, many natural and artificial sys…
GoRINNs: Godunov-Riemann Informed Neural Networks for Learning Hyperbolic Conservation Laws
Dimitrios G. Patsatzis, Mario di Bernardo, Lucia Russo +1
We present GoRINNs: numerical analysis-informed (shallow) neural networks for the solution of inverse problems of non-linear systems of conservation laws. GoRINNs is a hybrid/blend…