Guiding swarm behavior is one of important problems in the area of swarm intelligence. While in many multiagent systems, the local rules for each agent is difficult or impossible to be redesigned. Even for artificial systems, it is not easy to design simple local rules for each agent which can lead the group emerge desired collective behavior. In this chapter, we introduce a new method called “Soft Control” which does not need to change the underlying local rules of agents, but to add some special agents, called “shills” which can be controlled by us, into the system. It is a nondestructive intervention method because shills are still treated as normal agents by normal ones. The soft-control method is effectively applied to three different multiagent system models to guide the swarm behavior: (1) guide consensus of a Vicsek-like flocking model by adding one intelligent shill, (2) promote cooperation for a group of players that play the end-unknown repeated prisoner's dilemma game by adding a cooperating team of shill plays and (3) add one or some shills to guide the collective opinion of the DeGroot model system.

Chapter Contents:

• Abstract
• 13.1 Introduction
• 13.2 Related works
• 13.3 Guiding flocking swarm by adding one intelligent shill
• 13.3.1 Model—the Vicsek model
• 13.3.2 Model with soft control
• 13.3.2.1 The first soft-control strategy
• 13.3.2.2 The second soft-control strategy—"consistent moving"
• 13.3.2.3 Algorithm
• 13.3.2.4 Analysis
• 13.3.2.5 Computer simulations
• 13.4 Guiding a group of game players by adding shills to promote cooperation
• 13.4.1 Model—the multiperson repeated prisoner's dilemma game
• 13.4.2 Model with shills
• 13.4.2.1 The shill strategy
• 13.4.2.2 Computer simulations
• 13.5 Guiding collective opinion by adding shills
• 13.5.1 Model—the DeGroot model
• 13.5.2 Model with evolvable-opinion shills
• 13.5.2.1 Undirected neighborhood graph
• 13.5.2.2 Directed neighborhood graph
• 13.5.3 Model with fixed-opinion shills
• 13.6 Conclusions
• Acknowledgments
• References

Inspec keywords: social sciences; game theory; multi-agent systems; multi-robot systems

Other keywords: multiagent systems; different multiagent system models; special agents; nondestructive intervention method; swarm intelligence; (1) guide consensus; swarm behavior; soft control; soft-control method; artificial systems; normal agents; shills; collective behavior; intelligent shill; simple local rules; underlying local rules; DeGroot model system

Subjects: Optimisation techniques; Combinatorial mathematics; Game theory; Expert systems and other AI software and techniques