Efficient Opinion Sharing in Large Decentralised Teams

In this paper we present an approach for improving the accu-racy of shared opinions in a large decentralised team. Specif-ically, our solution optimises the opinion sharing process in order to help the majority of agents to form the correct opin-ion about a state of a common subject of interest, given only few agents with noisy sensors in the large team. We build on existing research that has examined models of this opinion sharing problem and shown the existence of optimal parame-ters where incorrect opinions are filtered out during the shar-ing process. In order to exploit this collective behaviour in complex networks, we present a new decentralised algorithm that allows each agent to gradually regulate the importance of its neighbours ’ opinions (their social influence). This leads the system to the optimised state in which agents are mos