3 papers
eess.SY2025
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…
cond-mat.soft2025
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…
eess.SY2024
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…