4 citations · 4 across the 4 of their papers we have counts for
5 papers
Hierarchical Learning-Based Control for Multi-Agent Shepherding of Stochastic Autonomous Agents
Italo Napolitano, Stefano Covone, Andrea Lama +2
Multi-agent shepherding represents a challenging distributed control problem where herder agents must coordinate to guide independently moving targets to desired spatial configurat…
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…
Emergent Cooperative Strategies for Multi-Agent Shepherding via Reinforcement Learning
Italo Napolitano, Andrea Lama, Francesco De Lellis +1
We present a decentralized reinforcement learning (RL) approach to address the multi-agent shepherding control problem, departing from the conventional assumption of cohesive targe…
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…