Norm Emergence through Conflict-Blocking Interactions in Industrial Internet of Things Environments.

Abstract

Norms have been effectively utilized to facilitate smooth interactions among agents. Norms are usually the global data that agents cannot directly access in complex environments; instead, norms can only be indirectly accessed by agents via maintaining their own beliefs about norms. Establishing norms using decentralized interaction-based methods has attracted much attention. However, the current methods overlook Industrial Internet of Things (IIoT) environments. In IIoT, there is a prevalent feature called "conflict-blocking", where agents' conflicting action strategies can block an interaction from being completed or even cause danger. To facilitate norm emergence in IIoT, we propose a framework to support agent decisions in conflict-blocking interactions. The framework aids in achieving system scalability by integrating the fusion of agent beliefs about norms. We prove that the proposed framework guarantees norm emergence. We also theoretically and experimentally analyze the time required for norm emergence under the influence of various factors, such as the number of agents. A vehicle movement simulator is also developed to vividly illustrate the process of norm emergence.