Flocking With Informed Agents Based on Incomplete Information

In this study, the problem of multi-agent flocking with partially informed agents is investigated, by considering the incomplete information factor in a flocking process. Incomplete information includes two aspects: receiver and sender. One is resisted or distorted information by the agents when they receive information from the virtual leader or others, and the other is passive loss of information sent by the virtual leader or others to the agents. In a flocking process with a fraction of informed agents, to make informed agents drive more uninformed agents to track the virtual leader, we first discuss the derivative of the potential function in the flocking algorithm: the force function. The relationship between repulsion and attraction among agents is directly shown. Subsequently, an improved flocking algorithm is proposed based on Morse potential function. The stability of the algorithm is proved by using the Lyapunov stability theorem and LaSalle’s invariance principle. Consider the initial distribution of agents with low connectivity and density, based on the above modified algorithm, a novel method of selecting informed agents as propagandists is presented. Propagandists are created in the vicinity of virtual leaders. Before flocking, propagandists move regularly within an arbitrarily distributed group, disseminating information to other uninformed agents. This approach can reduce the unfavorable effects caused by incomplete information. Eventually, the simulation results show that even though only one informed agent is selected as the propagandist, most agents can track the common objective.