Detecting Emergent Behaviors with an Expert System in Complex System

The notion of emergence is one of the most discussed topics in the world today, understanding the causes of emergent behavior in terms of system components, their attributes, and their interactions is critical in order to influence the appearance of desired emergent properties and the reduction of any undesired effects. However, the inability to predict and control emergent phenomena prevents us from exploring its full potential. In addition, the article explores how interactions can be used as a metric to identify emergent behaviors in the Boids model and outlines the initial effects of a four step process: (1)representation and acquisition of simulation data and human knowledge, (2)Rule-based transformation of the data,(3)Building of the inference engine, (4)Learning process and emergence detection. Furthermore, the update of the rule base with new rules when a new unknown behavior appears. Since this is a part of ongoing research, future direction is also discussed.