Stochastic Recruitment: A Limited-Feedback Control Policy for Large Ensemble Systems
Abstract
This paper is about stochastic recruitment, a control architecture for centrally controlling the ensemble behavior of many identical agents, in a manner similar to motor recruitment in skeletal muscles. Each agent has a finite set of behaviors or states, which can be switched based on a broadcast command. By switching randomly between states with a centrally determined probability, it is possible to designate the number of agents in each state. This paper covers stochastic recruitment policies for the case when little or no feedback is available from the system. Feed-forward control policies based on rate equilibria are presented, with an analysis of the performance trade-offs inherent in the problem. Minimal feedback control laws are also discussed, and a policy is presented which minimizes the expected convergence time of the system given only the ability to halt the system when the desired output has been achieved.