Soft Control on Collective Behavior of a Group of Autonomous Agents By a Shill Agent

Abstract

This paper asks a new question: how can we control the collective behavior of self-organized multi-agent systems? We try to answer the question by proposing a new notion called 'Soft Control', which keeps the local rule of the existing agents in the system. We show the feasibility of soft control by a case study. Consider the simple but typical distributed multi-agent model proposed by Vicsek et al. for flocking of birds: each agent moves with the same speed but with different headings which are updated using a local rule based on the average of its own heading and the headings of its neighbors.Most studies of this model are about the self-organized collective behavior, such as synchronization of headings. We want to intervene in the collective behavior (headings) of the group by soft control. A specified method is to add a special agent, called a 'Shill', which can be controlled by us but is treated as an ordinary agent by other agents. We construct a control law for the shill so that it can synchronize the whole group to an objective heading. This control law is proved to be effective analytically and numerically. Note that soft control is different from the approach of distributed control. It is a natural way to intervene in the distributed systems. It may bring out many interesting issues and challenges on the control of complex systems.

Outdoor flocking and formation flight with autonomous aerial robots

“…The bounding walls are pre-defined globally, but they appear as local attractive shill agents [30] that try to pull units back towards the center of the flight area through virtual velocity alignment:…”

Leader-based versus soft control of multi-agent swarms

“…The study of leadership also plays an important role in ethology, where recent papers presented experimental validation of theoretical results [3]. In parallel, due to numerous applications, the control of a swarm via shill agents (referred to as "soft-control" [4]) is becoming very popular in robotics and ethology [5,6]. This paper attempts a classification of the different types of swarm control mechanisms based on special agents.…”

Soft Control for Swarm Aggregations

“…Collective behavior is one of the fundamental and difficult topics of the study of complex systems. We classify the researches on collective behavior into three categories [5].…”

“…Then soft control may be the feasible way to intervene in the collective behavior. Han Jing et al proposed the tactics of "soft control" in Boid model first [5], then Pan Fu-chen et al proposed the tactics of "soft control" in swam system [6], which controlled the swarm center to an expect position by controlling the original position of controlled intelligent agents, given a control law and dis-cussed the optimization of convergence time by particle swarm optimization algorithm for several intelligent agents.…”