Self-Organizing Control Mechanisms According to Information Confidence for Improving Performance

Self-organizing systems are focused on to realize novel network control systems that are highly scalable, adaptable, and robust. However, the uncertainty of information makes it difficult for self-organizing systems to work appropriately, thereby degrading their performance. It is necessary to improve the performance of self-organizing systems while retaining their advantages. Therefore, we apply the concept of flexible leadership of the collective decision-making in human groups to self-organizing control mechanisms. By incorporating this concept, agents dynamically and flexibly change their role (leader or follower) according to the confidence of their own information, which increases decision accuracy under information uncertainty. We propose a channel-selection mechanism based on collective decision-making in accordance with information confidence. Simulation experiments show that the proposed mechanism improves the performance of network systems while retaining the high adaptability.