Belief Control Strategies for Interactions Over Weakly-Connected Graphs

• Main Authors: Hawraa Salami, Bicheng Ying, Ali H. Sayed
• Format: Article
• Language: English
• Published: IEEE 2021-01-01
• Series: IEEE Open Journal of Signal Processing
• Subjects: Social networks; diffusion learning; influential agents; leader-follower relation; belief control; weak graph
• Online Access: https://ieeexplore.ieee.org/document/9432750/

In diffusion social learning over weakly-connected graphs, it has been shown recently that influential agents shape the beliefs of non-influential agents. This paper analyzes this mechanism more closely and addresses two main questions. First, the article examines how much freedom influential agents have in controlling the beliefs of the receiving agents, namely, whether receiving agents can be driven to arbitrary beliefs and whether the network structure limits the scope of control by the influential agents. Second, even if there is a limit to what influential agents can accomplish, this article develops mechanisms by which they can lead receiving agents to adopt certain beliefs. These questions raise interesting possibilities about belief control over networked agents. Once addressed, one ends up with design procedures that allow influential agents to drive other agents to endorse particular beliefs regardless of their local observations or convictions. The theoretical findings are illustrated by means of examples.