Sensing Emergence in Complex Systems

We propose the Sensing of Emergent behavior in a Complex Adaptive System (SECAS), as an extension of our previous work Formal Agent-Based Simulation Framework (FABS). Using aggregated data from an array of proximity sensors, SECAS allows for the detection of complex behavior such as flocking of mobile robots or life forms. For validation, we develop an agent-based simulation model. Extensive simulation experiments using a wide range of randomly deployed sensors demonstrate the effectiveness of SECAS in the sensing of flocking.