Shepherding control and herdability in complex multiagent systems

2023/07/31 by Andrea Lama, Lama, Andrea, Mario di Bernardo +1 · 5 citations
Biochemistry, Genetics and Molecular Biology · Engineering · Social Sciences · #Diffusion and Search Dynamics #Evolutionary Game Theory and Cooperation #FOS: Electrical engineering #FOS: Physical sciences #Slime Mold and Myxomycetes Research #Statistical Mechanics (cond-mat.stat-mech) #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2307.16797

openalex publication_date 2023/07/31 · openalex created_date 2023/08/02 · openalex updated_date 2026/07/28

Abstract

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 towards a desired goal. We relax the strong assumptions of targets showing cohesive collective behavior in the absence of the herders, and herders owning global sensing capabilities. We find scaling laws linking the number of targets and minimum herders needed, and we unveil the existence of a critical threshold of the density of the targets, below which the number of herders needed for success significantly increases. We explain the existence of such a threshold in terms of the percolation of a suitably defined herdability graph and support our numerical evidence by deriving and analysing a PDE describing the herders dynamics in a simplified one-dimensional setting. Extensive numerical experiments validate our methodology.

Cited by

• Decentralized Shepherding of Non-Cohesive Swarms Through Cluttered Environments via Deep Reinforcement Learning
• Sparse shepherding control of large-scale multi-agent systems via Reinforcement Learning
• Optimal Control Strategies for Multi-Agent Sheep Herding
• Hierarchical Learning-Based Control for Multi-Agent Shepherding of Stochastic Autonomous Agents
• Multi-Robot Cooperative Herding through Backstepping Control Barrier Functions

Related

• Preliminary results on the herdability of complex multiagent systems via local information
• A Continuification-Based Control Solution for Large-Scale Shepherding
• Emergent Cooperative Strategies for Multi-Agent Shepherding via Reinforcement Learning
• Decentralized Shepherding of Non-Cohesive Swarms Through Cluttered Environments via Deep Reinforcement Learning
• Controlling herding in minority game systems