This article presents a novel control strategy to herd groups of noncooperative evaders by
means of a team of robotic herders. In herding problems, the motion of the evaders is …

This study investigated the utility of supervised machine learning (SML) and explainable
artificial intelligence (AI) techniques for modeling and understanding human decision …

This study investigated whether dynamical perceptual-motor primitives (DPMPs) could also
be used to capture human navigation in a first-person herding task. To achieve this aim …

We study the shepherding control problem where a group of “herders” need to orchestrate
their collective behavior in order to steer the dynamics of a group of “target” agents towards …

This article presents a distributed control strategy for herding groups of evaders toward a
predefined goal region using a team of robotic herders. In herding problems, evaders tend to …

We analyze the problem of controlling a multiagent system with additive white noise through
parsimonious interventions on a selected subset of the agents (leaders). For such a …

Motivated by the applications in leader-follower multi-agent dynamics, a class of optimal
control problems is investigated, where the goal is to influence the behavior of a given …

Introduction: Geometric pattern formation is crucial in many tasks involving large-scale multi-
agent systems. Examples include mobile agents performing surveillance, swarms of drones …

This paper presents a distributed control strategy, named Triangle Formation (TF) algorithm,
for a group of robots. The algorithm is based on a geometric approach and enables three …

Abstract Recent innovations in Deep Reinforcement Learning (DRL) and Artificial
Intelligence (AI) techniques have allowed for the development of artificial agents that can …