Controlling Noisy Herds

Individual sheep instinctively flee from shepherd dogs, yet in larger groups, they adopt a ‘selfish herd strategy,’ clustering together to minimize risk. This well-known collective behavior falters in small groups (N<5), where sheep unpredictably oscillate between fleeing and clustering. In this talk, we will discuss the physics of controlling such small N, noisy collectives, using the interaction between sheep and shepherd dogs as a case study. We focus on two key tasks: ‘the drive,’ which involves herding the group of sheep together, and ‘the shed,’ the act of splitting the group into two subgroups. Through mathematical modeling and field observations, we show that the key to controlling these erratic small groups lies in exploiting their inherent stochasticity. Our mechanistic framework not only offers a deeper understanding of animal herd dynamics but also provides valuable insights into controlling dynamic and heterogeneous systems across various disciplines, from swarm robots to public policy.