Artificial Intelligence-Enabled Authority Game for Human–Swarm Control: Toward Adaptive Levels of Autonomy

Level of autonomy (LOA) has become one of the determining factors for human-swarm control. Because of the autonomy restriction in current unmanned system, the human-swarm cooperation has gradually become the common and necessary task mode. To enable the adaptive LOA in the heterogenous team, we present a human-swarm authority game model to make decisions on the LOA. The goal of this approach is to obtain the suitable LOA in the dynamic task environment on the basis of the swarm performance and operator trust. Due to the uncertainty of the human trust, a trust model toward swarm is built via imitation learning (IL) method. Thus, the optimal strategy on the LOA could be calculated by the human-swarm evolutionary game model considering the cases with incomplete information. The simulation experiments are conducted on the three-dimension virtual platform. The simulation results show the correctness and accuracy of the prediction model.